Abstract is missing.
- Hermitian matrices for clustering directed graphs: insights and applicationsMihai Cucuringu, Huan Li, He Sun 0001, Luca Zanetti. [doi]
- Linearly Convergent Frank-Wolfe without Line-SearchFabian Pedregosa, Geoffrey Négiar, Armin Askari, Martin Jaggi. 1-10 [doi]
- Guarantees of Stochastic Greedy Algorithms for Non-monotone Submodular Maximization with Cardinality ConstraintShinsaku Sakaue. 11-21 [doi]
- On Maximization of Weakly Modular Functions: Guarantees of Multi-stage Algorithms, Tractability, and HardnessShinsaku Sakaue. 22-33 [doi]
- Adaptive Trade-Offs in Off-Policy LearningMark Rowland, Will Dabney, Rémi Munos. 34-44 [doi]
- Conditional Importance Sampling for Off-Policy LearningMark Rowland, Anna Harutyunyan, Hado van Hasselt, Diana Borsa, Tom Schaul, Rémi Munos, Will Dabney. 45-55 [doi]
- Multiplicative Gaussian Particle FilterXuan Su, Wee Sun Lee, Zhen Zhang. 56-65 [doi]
- Stretching the Effectiveness of MLE from Accuracy to Bias for Pairwise ComparisonsJingyan Wang 0001, Nihar B. Shah, R. Ravi 0001. 66-76 [doi]
- Fast and Accurate Ranking RegressionIlkay Yildiz, Jennifer G. Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis. 77-88 [doi]
- Tight Analysis of Privacy and Utility Tradeoff in Approximate Differential PrivacyQuan Geng, Wei Ding, Ruiqi Guo, Sanjiv Kumar. 89-99 [doi]
- Long-and Short-Term Forecasting for Portfolio Selection with Transaction CostsGuy Uziel, Ran El-Yaniv. 100-110 [doi]
- Nonparametric Sequential Prediction While Deep Learning the KernelGuy Uziel. 111-121 [doi]
- Improving Maximum Likelihood Training for Text Generation with Density Ratio EstimationYuxuan Song, Ning Miao, Hao Zhou, Lantao Yu, Mingxuan Wang, Lei Li 0018. 122-132 [doi]
- A Double Residual Compression Algorithm for Efficient Distributed LearningXiaorui Liu, Yao Li, Jiliang Tang, Ming Yan. 133-143 [doi]
- Asynchronous Gibbs SamplingAlexander Terenin, Daniel Simpson, David Draper. 144-154 [doi]
- Learning Fair Representations for Kernel ModelsZilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar. 155-166 [doi]
- A Nonparametric Off-Policy Policy GradientSamuele Tosatto, Joao Carvalho, Hany Abdulsamad, Jan Peters 0001. 167-177 [doi]
- Non-Parametric Calibration for ClassificationJonathan Wenger, Hedvig Kjellström, Rudolph Triebel. 178-190 [doi]
- Minimax Testing of Identity to a Reference Ergodic Markov ChainGeoffrey Wolfer, Aryeh Kontorovich. 191-201 [doi]
- A Linear-time Independence Criterion Based on a Finite Basis ApproximationLongfei Yan, W. Bastiaan Kleijn, Thushara D. Abhayapala. 202-212 [doi]
- Minimax Bounds for Structured Prediction Based on Factor GraphsKevin Bello, Asish Ghoshal, Jean Honorio. 213-222 [doi]
- On the Convergence of SARAH and BeyondBingcong Li, Meng Ma, Georgios B. Giannakis. 223-233 [doi]
- Uncertainty in Neural Networks: Approximately Bayesian EnsemblingTim Pearce, Felix Leibfried, Alexandra Brintrup. 234-244 [doi]
- LIBRE: Learning Interpretable Boolean Rule EnsemblesGraziano Mita, Paolo Papotti, Maurizio Filippone, Pietro Michiardi. 245-255 [doi]
- Marginal Densities, Factor Graph Duality, and High-Temperature Series ExpansionsMehdi Molkaraie. 256-265 [doi]
- Neighborhood Growth Determines Geometric Priors for Relational Representation LearningMelanie Weber 0001. 266-276 [doi]
- Fair Decisions Despite Imperfect PredictionsNiki Kilbertus, Manuel Gomez-Rodriguez, Bernhard Schölkopf, Krikamol Muandet, Isabel Valera. 277-287 [doi]
- A Characterization of Mean Squared Error for Estimator with BaggingMartin Mihelich, Charles Dognin, Yan Shu, Michael Blot. 288-297 [doi]
- Uncertainty Quantification for Sparse Deep LearningYuexi Wang, Veronika Rocková. 298-308 [doi]
- Minimizing Dynamic Regret and Adaptive Regret SimultaneouslyLijun Zhang 0005, Shiyin Lu, Tianbao Yang. 309-319 [doi]
- A Stein Goodness-of-fit Test for Directional DistributionsWenkai Xu, Takeru Matsuda. 320-330 [doi]
- Unsupervised Neural Universal Denoiser for Finite-Input General-Output Noisy ChannelTaeeon Park, Taesup Moon. 331-340 [doi]
- Leave-One-Out Cross-Validation for Bayesian Model Comparison in Large DataMåns Magnusson, Aki Vehtari, Johan Jonasson, Michael Riis Andersen. 341-351 [doi]
- Robust Importance Weighting for Covariate ShiftFengpei Li, Henry Lam, Siddharth Prusty. 352-362 [doi]
- Adaptive Online Kernel Sampling for Vertex ClassificationPeng Yang, Ping Li. 363-373 [doi]
- A Hybrid Stochastic Policy Gradient Algorithm for Reinforcement LearningNhan H. Pham, Lam M. Nguyen, Dzung T. Phan, Phuong Ha Nguyen, Marten van Dijk, Quoc Tran-Dinh. 374-385 [doi]
- Stopping criterion for active learning based on deterministic generalization boundsHideaki Ishibashi, Hideitsu Hino. 386-397 [doi]
- Ivy: Instrumental Variable Synthesis for Causal InferenceZhaobin Kuang, Frederic Sala, Nimit Sharad Sohoni, Sen Wu 0002, Aldo Córdova-Palomera, Jared Dunnmon, James Priest, Christopher Ré. 398-410 [doi]
- High Dimensional Robust Sparse RegressionLiu Liu, Yanyao Shen, Tianyang Li, Constantine Caramanis. 411-421 [doi]
- Nested-Wasserstein Self-Imitation Learning for Sequence GenerationRuiyi Zhang, Changyou Chen, Zhe Gan, Zheng Wen, Wenlin Wang, Lawrence Carin. 422-433 [doi]
- Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse OptimizationHuang Fang, Zhenan Fan, Yifan Sun, Michael P. Friedlander. 434-444 [doi]
- Recommendation on a Budget: Column Space Recovery from Partially Observed Entries with Random or Active SamplingCarolyn Kim, Mohsen Bayati. 445-455 [doi]
- Fast Noise Removal for k-Means ClusteringSungjin Im, Mahshid Montazer Qaem, Benjamin Moseley, Xiaorui Sun, Rudy Zhou. 456-466 [doi]
- Sketching Transformed Matrices with Applications to Natural Language ProcessingYingyu Liang, Zhao Song, Mengdi Wang, Lin Yang, Xin Yang 0017. 467-481 [doi]
- Unconditional Coresets for Regularized Loss MinimizationAlireza Samadian, Kirk Pruhs, Benjamin Moseley, Sungjin Im, Ryan R. Curtin. 482-492 [doi]
- ASAP: Architecture Search, Anneal and PruneAsaf Noy, Niv Nayman, Tal Ridnik, Nadav Zamir, Sivan Doveh, Itamar Friedman, Raja Giryes, Lihi Zelnik. 493-503 [doi]
- Understanding Generalization in Deep Learning via Tensor MethodsJingling Li, Yanchao Sun, Jiahao Su, Taiji Suzuki, Furong Huang. 504-515 [doi]
- Accelerating Gradient Boosting MachinesHaihao Lu, Sai Praneeth Karimireddy, Natalia Ponomareva, Vahab S. Mirrokni. 516-526 [doi]
- Online Binary Space Partitioning ForestsXuhui Fan, Bin Li, Scott A. Sisson. 527-537 [doi]
- Sparse Hilbert-Schmidt Independence Criterion RegressionBenjamin Poignard, Makoto Yamada. 538-548 [doi]
- Sharp Thresholds of the Information Cascade Fragility Under a Mismatched ModelWasim Huleihel, Ofer Shayevitz. 549-558 [doi]
- Optimal sampling in unbiased active learningHenrik Imberg, Johan Jonasson, Marina Axelson-Fisk. 559-569 [doi]
- The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth measureGuillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémençon. 570-579 [doi]
- Diameter-based Interactive Structure DiscoveryChristopher Tosh, Daniel Hsu 0001. 580-590 [doi]
- Utility/Privacy Trade-off through the lens of Optimal TransportEtienne Boursier, Vianney Perchet. 591-601 [doi]
- A Lyapunov analysis for accelerated gradient methods: from deterministic to stochastic caseMaxime Laborde, Adam M. Oberman. 602-612 [doi]
- Interpretable Deep Gaussian Processes with MomentsChi-Ken Lu, Scott Cheng-Hsin Yang, Xiaoran Hao, Patrick Shafto. 613-623 [doi]
- Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value FunctionsLars Buesing, Nicolas Heess, Theophane Weber. 624-634 [doi]
- Accelerated Bayesian Optimisation through Weight-Prior TuningAlistair Shilton, Sunil Gupta 0001, Santu Rana, Pratibha Vellanki, Cheng Li 0003, Svetha Venkatesh, Laurence Park, Alessandra Sutti, David Rubin, Thomas Dorin, Alireza Vahid, Murray Height, Teo Slezak. 635-645 [doi]
- Variance Reduction for Evolution Strategies via Structured Control VariatesYunhao Tang, Krzysztof Choromanski, Alp Kucukelbir. 646-656 [doi]
- Optimization of Graph Total Variation via Active-Set-based Combinatorial ReconditioningZhenzhang Ye, Thomas Möllenhoff, Tao Wu 0006, Daniel Cremers. 657-668 [doi]
- Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk MinimizationKenji Kawaguchi, Haihao Lu. 669-679 [doi]
- A Unified Theory of SGD: Variance Reduction, Sampling, Quantization and Coordinate DescentEduard A. Gorbunov, Filip Hanzely, Peter Richtárik. 680-690 [doi]
- Entropy Weighted Power k-Means ClusteringSaptarshi Chakraborty, Debolina Paul, Swagatam Das, Jason Xu. 691-701 [doi]
- Identifying and Correcting Label Bias in Machine LearningHeinrich Jiang, Ofir Nachum. 702-712 [doi]
- AsyncQVI: Asynchronous-Parallel Q-Value Iteration for Discounted Markov Decision Processes with Near-Optimal Sample ComplexityYibo Zeng, Fei Feng, Wotao Yin. 713-723 [doi]
- Active Community Detection with Maximal Expected Model ChangeDan Kushnir, Benjamin Mirabelli. 724-734 [doi]
- RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confoundersTakashi Nicholas Maeda, Shohei Shimizu. 735-745 [doi]
- A Simple Approach for Non-stationary Linear BanditsPeng Zhao, Lijun Zhang, Yuan Jiang, Zhi-Hua Zhou. 746-755 [doi]
- Distributionally Robust Formulation and Model Selection for the Graphical LassoPedro Cisneros-Velarde, Alexander Petersen, Sang-Yun Oh. 756-765 [doi]
- Efficient Spectrum-Revealing CUR Matrix DecompositionCheng Chen, Ming Gu, Zhihua Zhang, Weinan Zhang 0001, Yong Yu. 766-775 [doi]
- Graph DNA: Deep Neighborhood Aware Graph Encoding for Collaborative FilteringLiwei Wu, Hsiang-Fu Yu, Nikhil Rao, James Sharpnack, Cho-Jui Hsieh. 776-787 [doi]
- Characterization of Overlap in Observational StudiesMichael Oberst, Fredrik D. Johansson, Dennis Wei, Tian Gao, Gabriel Brat, David A. Sontag, Kush R. Varshney. 788-798 [doi]
- Modular Block-diagonal Curvature Approximations for Feedforward ArchitecturesFelix Dangel, Stefan Harmeling, Philipp Hennig. 799-808 [doi]
- A Unified Statistically Efficient Estimation Framework for Unnormalized ModelsMasatoshi Uehara, Takafumi Kanamori, Takashi Takenouchi, Takeru Matsuda. 809-819 [doi]
- More Powerful Selective Kernel Tests for Feature SelectionJen Ning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira. 820-830 [doi]
- Imputation estimators for unnormalized models with missing dataMasatoshi Uehara, Takeru Matsuda, Jae-Kwang Kim. 831-841 [doi]
- Wasserstein Style TransferYoussef Mroueh. 842-852 [doi]
- Elimination of All Bad Local Minima in Deep LearningKenji Kawaguchi, Leslie Pack Kaelbling. 853-863 [doi]
- Fully Decentralized Joint Learning of Personalized Models and Collaboration GraphsValentina Zantedeschi, Aurélien Bellet, Marc Tommasi. 864-874 [doi]
- Formal Limitations on the Measurement of Mutual InformationDavid McAllester, Karl Stratos. 875-884 [doi]
- Scalable Feature Selection for (Multitask) Gradient Boosted TreesCuize Han, Nikhil Rao, Daria Sorokina, Karthik Subbian. 885-894 [doi]
- Model-Agnostic Counterfactual Explanations for Consequential DecisionsAmir-Hossein Karimi, Gilles Barthe, Borja Balle, Isabel Valera. 895-905 [doi]
- Obfuscation via Information Density EstimationHsiang Hsu, Shahab Asoodeh, Flávio du Pin Calmon. 906-917 [doi]
- Linear Dynamics: Clustering without identificationChloe Ching-Yun Hsu, Michaela Hardt, Moritz Hardt. 918-929 [doi]
- Low-rank regularization and solution uniqueness in over-parameterized matrix sensingKelly Geyer, Anastasios Kyrillidis, Amir Kalev. 930-940 [doi]
- Robustness for Non-Parametric Classification: A Generic Attack and DefenseYao-Yuan Yang, Cyrus Rashtchian, Yizhen Wang, Kamalika Chaudhuri. 941-951 [doi]
- Contextual Online False Discovery Rate ControlShiyun Chen, Shiva Prasad Kasiviswanathan. 952-961 [doi]
- Sequential no-Substitution k-Median-ClusteringTom Hess, Sivan Sabato. 962-972 [doi]
- Robust Learning from Discriminative Feature FeedbackSanjoy Dasgupta, Sivan Sabato. 973-982 [doi]
- Kernel Conditional Density OperatorsIngmar Schuster, Mattes Mollenhauer, Stefan Klus, Krikamol Muandet. 993-1004 [doi]
- Learning Overlapping Representations for the Estimation of Individualized Treatment EffectsYao Zhang, Alexis Bellot, Mihaela van der Schaar. 1005-1014 [doi]
- Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian OptimizationXingchen Ma, Matthew B. Blaschko. 1015-1025 [doi]
- Asymptotic Analysis of Sampling Estimators for Randomized Numerical Linear Algebra AlgorithmsPing Ma, Xinlian Zhang, Xin-xing, Jingyi Ma, Michael W. Mahoney. 1026-1035 [doi]
- The Fast Loaded Dice Roller: A Near-Optimal Exact Sampler for Discrete Probability DistributionsFeras Saad, Cameron E. Freer, Martin Rinard, Vikash Mansinghka. 1036-1046 [doi]
- A Fast Anderson-Chebyshev Acceleration for Nonlinear OptimizationZhize Li, Jian Li 0015. 1047-1057 [doi]
- Black Box Submodular Maximization: Discrete and Continuous SettingsLin Chen, Mingrui Zhang, Hamed Hassani, Amin Karbasi. 1058-1070 [doi]
- Corruption-Tolerant Gaussian Process Bandit OptimizationIlija Bogunovic, Andreas Krause 0001, Jonathan Scarlett. 1071-1081 [doi]
- On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning AlgorithmsAlireza Fallah 0001, Aryan Mokhtari, Asuman E. Ozdaglar. 1082-1092 [doi]
- Alternating Minimization Converges Super-Linearly for Mixed Linear RegressionAvishek Ghosh, Kannan Ramchandran. 1093-1103 [doi]
- Learning Gaussian Graphical Models via Multiplicative WeightsAnamay Chaturvedi, Jonathan Scarlett. 1104-1114 [doi]
- Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction ApproachNan Lu, Tianyi Zhang, Gang Niu, Masashi Sugiyama. 1115-1125 [doi]
- Infinitely deep neural networks as diffusion processesStefano Peluchetti, Stefano Favaro. 1126-1136 [doi]
- Stable behaviour of infinitely wide deep neural networksStefano Peluchetti, Stefano Favaro, Sandra Fortini. 1137-1146 [doi]
- Neural Topic Model with Attention for Supervised LearningXinyi Wang, Yi Yang. 1147-1156 [doi]
- Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble MethodPengzhou Wu, Kenji Fukumizu. 1157-1167 [doi]
- Stochastic Bandits with Delay-Dependent PayoffsLeonardo Cella, Nicolò Cesa-Bianchi. 1168-1177 [doi]
- Risk Bounds for Learning Multiple Components with Permutation-Invariant LossesFabien Lauer. 1178-1187 [doi]
- Balancing Learning Speed and Stability in Policy Gradient via Adaptive ExplorationMatteo Papini, Andrea Battistello, Marcello Restelli. 1188-1199 [doi]
- Independent Subspace Analysis for Unsupervised Learning of Disentangled RepresentationsJan Stuehmer, Richard E. Turner, Sebastian Nowozin. 1200-1210 [doi]
- A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among PlayersAbbas Mehrabian, Etienne Boursier, Emilie Kaufmann, Vianney Perchet. 1211-1221 [doi]
- Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal TransportFrançois-Pierre Paty, Alexandre d'Aspremont, Marco Cuturi. 1222-1232 [doi]
- On Generalization Bounds of a Family of Recurrent Neural NetworksMinshuo Chen, Xingguo Li, Tuo Zhao. 1233-1243 [doi]
- Simulator Calibration under Covariate Shift with KernelsKeiichi Kisamori, Motonobu Kanagawa, Keisuke Yamazaki. 1244-1253 [doi]
- Convergence Rates of Gradient Descent and MM Algorithms for Bradley-Terry ModelsMilan Vojnovic, Se-Young Yun, Kaifang Zhou. 1254-1264 [doi]
- A Locally Adaptive Bayesian Cubature MethodMatthew Fisher, Chris Oates, Catherine E. Powell, Aretha L. Teckentrup. 1265-1275 [doi]
- Fast and Bayes-consistent nearest neighborsKlim Efremenko, Aryeh Kontorovich, Moshe Noivirt. 1276-1286 [doi]
- Explaining the Explainer: A First Theoretical Analysis of LIMEDamien Garreau, Ulrike von Luxburg. 1287-1296 [doi]
- A Continuous-time Perspective for Modeling Acceleration in Riemannian OptimizationFoivos Alimisis, Antonio Orvieto, Gary Bécigneul, Aurélien Lucchi. 1297-1307 [doi]
- Deep Active Learning: Unified and Principled Method for Query and TrainingChangjian Shui, Fan Zhou, Christian Gagné, Boyu Wang. 1308-1318 [doi]
- Sparse and Low-rank Tensor Estimation via Cubic SketchingsBotao Hao, Anru R. Zhang, Guang Cheng. 1319-1330 [doi]
- A nonasymptotic law of iterated logarithm for general M-estimatorsArnak S. Dalalyan, Nicolas Schreuder, Victor-Emmanuel Brunel. 1331-1341 [doi]
- Robust Stackelberg buyers in repeated auctionsThomas Nedelec, Clément Calauzènes, Vianney Perchet, Noureddine El Karoui. 1342-1351 [doi]
- Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep LearningSebastian Farquhar, Michael A. Osborne, Yarin Gal. 1352-1362 [doi]
- Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point ProcessesKrzysztof Choromanski, Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang. 1363-1374 [doi]
- Fast and Furious Convergence: Stochastic Second Order Methods under InterpolationSi Yi Meng, Sharan Vaswani, Issam Hadj Laradji), Mark Schmidt 0001, Simon Lacoste-Julien. 1375-1386 [doi]
- Two-sample Testing Using Deep LearningMatthias Kirchler, Shahryar Khorasani, Marius Kloft, Christoph Lippert. 1387-1398 [doi]
- RATQ: A Universal Fixed-Length Quantizer for Stochastic OptimizationPrathamesh Mayekar, Himanshu Tyagi. 1399-1409 [doi]
- Rep the Set: Neural Networks for Learning Set RepresentationsKonstantinos Skianis, Giannis Nikolentzos, Stratis Limnios, Michalis Vazirgiannis. 1410-1420 [doi]
- A Multiclass Classification Approach to Label RankingRobin Vogel, Stéphan Clémençon. 1421-1430 [doi]
- Conservative Exploration in Reinforcement LearningEvrard Garcelon, Mohammad Ghavamzadeh, Alessandro Lazaric, Matteo Pirotta. 1431-1441 [doi]
- A principled approach for generating adversarial images under non-smooth dissimilarity metricsAram-Alexandre Pooladian, Chris Finlay, Tim Hoheisel, Adam M. Oberman. 1442-1452 [doi]
- Regularization via Structural Label SmoothingWeizhi Li, Gautam Dasarathy, Visar Berisha. 1453-1463 [doi]
- Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm BallsJiacheng Zhuo, Qi Lei, Alex Dimakis, Constantine Caramanis. 1464-1474 [doi]
- Linear Convergence of Adaptive Stochastic Gradient DescentYuege Xie, Xiaoxia Wu, Rachel Ward. 1475-1485 [doi]
- Contextual Combinatorial Volatile Multi-armed Bandit with Adaptive DiscretizationAndi Nika, Sepehr Elahi, Cem Tekin. 1486-1496 [doi]
- A Unified Analysis of Extra-gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point ApproachAryan Mokhtari, Asuman E. Ozdaglar, Sarath Pattathil. 1497-1507 [doi]
- Bandit Convex Optimization in Non-stationary EnvironmentsPeng Zhao, Guanghui Wang, Lijun Zhang, Zhi-Hua Zhou. 1508-1518 [doi]
- Decentralized Multi-player Multi-armed Bandits with No Collision InformationChengshuai Shi, Wei Xiong, Cong Shen, Jing Yang. 1519-1528 [doi]
- Bayesian Image Classification with Deep Convolutional Gaussian ProcessesVincent Dutordoir, Mark van der Wilk, Artem Artemev, James Hensman. 1529-1539 [doi]
- Optimizing Millions of Hyperparameters by Implicit DifferentiationJonathan Lorraine, Paul Vicol, David Duvenaud. 1540-1552 [doi]
- A Topology Layer for Machine LearningRickard Brüel Gabrielsson, Bradley J. Nelson, Anjan Dwaraknath, Primoz Skraba. 1553-1563 [doi]
- Differentiable Feature Selection by Discrete RelaxationRishit Sheth, Nicoló Fusi. 1564-1572 [doi]
- Private Protocols for U-Statistics in the Local Model and BeyondJames Bell, Aurélien Bellet, Adrià Gascón, Tejas Kulkarni. 1573-1583 [doi]
- Automatic Differentiation of Some First-Order Methods in Parametric OptimizationSheheryar Mehmood, Peter Ochs. 1584-1594 [doi]
- DYNOTEARS: Structure Learning from Time-Series DataRoxana Pamfil, Nisara Sriwattanaworachai, Shaan Desai, Philip Pilgerstorfer, Konstantinos Georgatzis, Paul Beaumont, Bryon Aragam. 1595-1605 [doi]
- Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic SpacesDavid Alvarez-Melis, Youssef Mroueh, Tommi S. Jaakkola. 1606-1617 [doi]
- Competing Bandits in Matching MarketsLydia T. Liu, Horia Mania, Michael I. Jordan. 1618-1628 [doi]
- Revisiting the Landscape of Matrix FactorizationHossein Valavi, Sulin Liu, Peter J. Ramadge. 1629-1638 [doi]
- Value Preserving State-Action AbstractionsDavid Abel, Nate Umbanhowar, Khimya Khetarpal, Dilip Arumugam, Doina Precup, Michael L. Littman. 1639-1650 [doi]
- GP-VAE: Deep Probabilistic Time Series ImputationVincent Fortuin, Dmitry Baranchuk, Gunnar Rätsch, Stephan Mandt. 1651-1661 [doi]
- Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance ReductionBoyue Li, Shicong Cen, Yuxin Chen 0002, Yuejie Chi. 1662-1672 [doi]
- Optimized Score Transformation for Fair ClassificationDennis Wei, Karthikeyan Natesan Ramamurthy, Flávio du Pin Calmon. 1673-1683 [doi]
- Variational Autoencoders for Sparse and Overdispersed Discrete DataHe Zhao, Piyush Rai, Lan Du 0002, Wray L. Buntine, Dinh Phung, Mingyuan Zhou. 1684-1694 [doi]
- Spatio-temporal alignments: Optimal transport through space and timeHicham Janati, Marco Cuturi, Alexandre Gramfort. 1695-1704 [doi]
- Accelerating Smooth Games by Manipulating Spectral ShapesWaïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel. 1705-1715 [doi]
- Langevin Monte Carlo without smoothnessNiladri S. Chatterji, Jelena Diakonikolas, Michael I. Jordan, Peter L. Bartlett. 1716-1726 [doi]
- EM Converges for a Mixture of Many Linear RegressionsJeongyeol Kwon, Constantine Caramanis. 1727-1736 [doi]
- Locally Accelerated Conditional GradientsJelena Diakonikolas, Alejandro Carderera, Sebastian Pokutta. 1737-1747 [doi]
- Coping With Simulators That Don't Always ReturnAndrew Warrington, Frank Wood, Saeid Naderiparizi. 1748-1758 [doi]
- Post-Estimation Smoothing: A Simple Baseline for Learning with Side InformationEsther Rolf, Michael I. Jordan, Benjamin Recht. 1759-1769 [doi]
- Equalized odds postprocessing under imperfect group informationPranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern. 1770-1780 [doi]
- The True Sample Complexity of Identifying Good ArmsJulian Katz-Samuels, Kevin G. Jamieson. 1781-1791 [doi]
- Validated Variational Inference via Practical Posterior Error BoundsJonathan H. Huggins, Mikolaj Kasprzak, Trevor Campbell, Tamara Broderick. 1792-1802 [doi]
- A Rule for Gradient Estimator Selection, with an Application to Variational InferenceTomas Geffner, Justin Domke. 1803-1812 [doi]
- Naive Feature Selection: Sparsity in Naive BayesArmin Askari, Alexandre d'Aspremont, Laurent El Ghaoui. 1813-1822 [doi]
- Fixed-confidence guarantees for Bayesian best-arm identificationXuedong Shang, Rianne de Heide, Pierre Ménard, Emilie Kaufmann, Michal Valko. 1823-1832 [doi]
- Learning Hierarchical Interactions at Scale: A Convex Optimization ApproachHussein Hazimeh 0001, Rahul Mazumder. 1833-1843 [doi]
- OSOM: A simultaneously optimal algorithm for multi-armed and linear contextual banditsNiladri S. Chatterji, Vidya Muthukumar, Peter L. Bartlett. 1844-1854 [doi]
- Optimization Methods for Interpretable Differentiable Decision Trees Applied to Reinforcement LearningAndrew Silva, Matthew C. Gombolay, Taylor W. Killian, Ivan Dario Jimenez Jimenez, Sung-Hyun Son. 1855-1865 [doi]
- Sharp Analysis of Expectation-Maximization for Weakly Identifiable ModelsRaaz Dwivedi, Nhat Ho, Koulik Khamaru, Martin J. Wainwright, Michael I. Jordan, Bin Yu 0001. 1866-1876 [doi]
- Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence TheoryJianyi Zhang, Ruiyi Zhang, Lawrence Carin, Changyou Chen. 1877-1887 [doi]
- Dynamical Systems Theory for Causal Inference with Application to Synthetic Control MethodsYi Ding, Panos Toulis. 1888-1898 [doi]
- RelatIF: Identifying Explanatory Training Samples via Relative InfluenceElnaz Barshan, Marc-Etienne Brunet, Gintare Karolina Dziugaite. 1899-1909 [doi]
- Ensemble Gaussian Processes with Spectral Features for Online Interactive Learning with ScalabilityQin Lu, Georgios Vasileios Karanikolas, Yanning Shen, Georgios B. Giannakis. 1910-1920 [doi]
- Distributionally Robust Bayesian Quadrature OptimizationThanh Tang Nguyen, Sunil Gupta 0001, Huong Ha, Santu Rana, Svetha Venkatesh. 1921-1931 [doi]
- Sparse Orthogonal Variational Inference for Gaussian ProcessesJiaxin Shi, Michalis K. Titsias, Andriy Mnih. 1932-1942 [doi]
- The Sylvester Graphical Lasso (SyGlasso)Yu Wang, Byoungwook Jang, Alfred Hero. 1943-1953 [doi]
- Frequentist Regret Bounds for Randomized Least-Squares Value IterationAndrea Zanette, David Brandfonbrener, Emma Brunskill, Matteo Pirotta, Alessandro Lazaric. 1954-1964 [doi]
- DAve-QN: A Distributed Averaged Quasi-Newton Method with Local Superlinear Convergence RateSaeed Soori, Konstantin Mishchenko, Aryan Mokhtari, Maryam Mehri Dehnavi, Mert Gürbüzbalaban. 1965-1976 [doi]
- Discrete Action On-Policy Learning with Action-Value CriticYuguang Yue, Yunhao Tang, Mingzhang Yin, Mingyuan Zhou. 1977-1987 [doi]
- Old Dog Learns New Tricks: Randomized UCB for Bandit ProblemsSharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton. 1988-1998 [doi]
- Thompson Sampling for Linearly Constrained BanditsVidit Saxena, Joakim Jaldén, Joseph Gonzalez 0001. 1999-2009 [doi]
- Sample Complexity of Reinforcement Learning using Linearly Combined Model EnsemblesAditya Modi 0002, Nan Jiang, Ambuj Tewari, Satinder P. Singh. 2010-2020 [doi]
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- Online Learning Using Only Peer PredictionYang Liu, David P. Helmbold. 2032-2042 [doi]
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- Stochastic Recursive Variance-Reduced Cubic Regularization MethodsDongruo Zhou, Quanquan Gu. 3980-3990 [doi]
- Better Long-Range Dependency By Bootstrapping A Mutual Information RegularizerYanshuai Cao, Peng Xu. 3991-4001 [doi]
- On the Completeness of Causal Discovery in the Presence of Latent Confounding with Tiered Background KnowledgeBryan Andrews. 4002-4011 [doi]
- One Sample Stochastic Frank-WolfeMingrui Zhang, Zebang Shen, Aryan Mokhtari, Hamed Hassani, Amin Karbasi. 4012-4023 [doi]
- Convex Geometry of Two-Layer ReLU Networks: Implicit Autoencoding and Interpretable ModelsTolga Ergen, Mert Pilanci. 4024-4033 [doi]
- A Robust Univariate Mean Estimator is All You NeedAdarsh Prasad, Sivaraman Balakrishnan, Pradeep Ravikumar. 4034-4044 [doi]
- Patient-Specific Effects of Medication Using Latent Force Models with Gaussian ProcessesLi-Fang Cheng, Bianca Dumitrascu, Michael Minyi Zhang, Corey Chivers, Michael Draugelis, Kai Li, Barbara E. Engelhardt. 4045-4055 [doi]
- Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type DataSimão Eduardo, Alfredo Nazábal, Christopher K. I. Williams, Charles A. Sutton. 4056-4066 [doi]
- Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensionsKamiar Rahnama Rad, Wenda Zhou, Arian Maleki. 4067-4077 [doi]
- A Diversity-aware Model for Majority Vote Ensemble AccuracyBob Durrant, Nick Lim. 4078-4087 [doi]
- Scaling up Kernel Ridge Regression via Locality Sensitive HashingAmir Zandieh, Navid Nouri, Ameya Velingker, Michael Kapralov, Ilya P. Razenshteyn. 4088-4097 [doi]
- Ordering-Based Causal Structure Learning in the Presence of Latent VariablesDaniel Irving Bernstein, Basil Saeed, Chandler Squires, Caroline Uhler. 4098-4108 [doi]
- Budget Learning via BracketingDurmus Alp Emre Acar, Aditya Gangrade, Venkatesh Saligrama. 4109-4119 [doi]
- Optimal Algorithms for Multiplayer Multi-Armed BanditsPo-An Wang, Alexandre Proutière, Kaito Ariu, Yassir Jedra, Alessio Russo. 4120-4129 [doi]
- AP-Perf: Incorporating Generic Performance Metrics in Differentiable LearningRizal Fathony, J. Zico Kolter. 4130-4140 [doi]
- Optimal Deterministic Coresets for Ridge RegressionPraneeth Kacham, David P. Woodruff. 4141-4150 [doi]
- Expressiveness and Learning of Hidden Quantum Markov ModelsSandesh Adhikary, Siddarth Srinivasan, Geoffrey J. Gordon, Byron Boots. 4151-4161 [doi]
- Solving the Robust Matrix Completion Problem via a System of Nonlinear EquationsYunfeng Cai, Ping Li. 4162-4172 [doi]
- Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic ApproximationShuhang Chen, Adithya M. Devraj, Ana Busic, Sean P. Meyn. 4173-4183 [doi]
- Stochastic Neural Network with Kronecker FlowChin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville. 4184-4194 [doi]
- Fair Correlation ClusteringSara Ahmadian, Alessandro Epasto, Ravi Kumar 0001, Mohammad Mahdian. 4195-4205 [doi]
- Towards Competitive N-gram SmoothingMoein Falahatgar, Mesrob I. Ohannessian, Alon Orlitsky, Venkatadheeraj Pichapati. 4206-4215 [doi]
- Multi-level Gaussian Graphical Models Conditional on CovariatesGi-Bum Kim, Seyoung Kim. 4216-4225 [doi]
- Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of componentsChristian Carmona, Geoff Nicholls. 4226-4235 [doi]
- Invertible Generative Modeling using Linear Rational SplinesHadi Mohaghegh Dolatabadi, Sarah M. Erfani, Christopher Leckie. 4236-4246 [doi]
- LdSM: Logarithm-depth Streaming Multi-label Decision TreesMaryam Majzoubi, Anna Choromanska. 4247-4257 [doi]
- Prior-aware Composition Inference for Spectral Topic ModelsMoontae Lee, David Bindel, David Mimno. 4258-4268 [doi]
- Variational Optimization on Lie Groups, with Examples of Leading (Generalized) Eigenvalue ProblemsMolei Tao, Tomoki Ohsawa. 4269-4280 [doi]
- Best-item Learning in Random Utility Models with Subset ChoicesBangalore) Aadirupa Saha, Bangalore) Aditya Gopalan. 4281-4291 [doi]
- Regularized Autoencoders via Relaxed Injective Probability FlowAbhishek Kumar, Ben Poole, Kevin Murphy 0002. 4292-4301 [doi]
- Stochastic Variance-Reduced Algorithms for PCA with Arbitrary Mini-Batch SizesCheolmin Kim, Diego Klabjan. 4302-4312 [doi]
- Gradient Descent with Early Stopping is Provably Robust to Label Noise for Overparameterized Neural NetworksMingchen Li, Mahdi Soltanolkotabi, Samet Oymak. 4313-4324 [doi]
- Scalable Nonparametric Factorization for High-Order Interaction EventsZhimeng Pan, Zheng Wang, Shandian Zhe. 4325-4335 [doi]
- Gaussianization FlowsChenlin Meng, Yang Song, Jiaming Song, Stefano Ermon. 4336-4345 [doi]
- Adaptive, Distribution-Free Prediction Intervals for Deep NetworksDanijel Kivaranovic, Kory D. Johnson, Hannes Leeb. 4346-4356 [doi]
- A Distributional Analysis of Sampling-Based Reinforcement Learning AlgorithmsPhilip Amortila, Doina Precup, Prakash Panangaden, Marc G. Bellemare. 4357-4366 [doi]
- Automatic Differentiation of Sketched RegressionHang Liao, Barak A. Pearlmutter, Vamsi K. Potluru, David P. Woodruff. 4367-4376 [doi]
- Sublinear Optimal Policy Value Estimation in Contextual BanditsWeihao Kong, Emma Brunskill, Gregory Valiant. 4377-4387 [doi]
- Budget-Constrained Bandits over General Cost and Reward DistributionsSemih Cayci, Atilla Eryilmaz, R. Srikant 0001. 4388-4398 [doi]
- Measuring Mutual Information Between All Pairs of Variables in Subquadratic ComplexityMohsen Ferdosi, Arash Gholami Davoodi, Hosein Mohimani. 4399-4409 [doi]
- Online Continuous DR-Submodular Maximization with Long-Term Budget ConstraintsOmid Sadeghi, Maryam Fazel. 4410-4419 [doi]
- Prediction Focused Topic Models via Feature SelectionJason Ren, Russell Kunes, Finale Doshi-Velez. 4420-4429 [doi]
- Accelerated Factored Gradient Descent for Low-Rank Matrix FactorizationDongruo Zhou, Yuan Cao, Quanquan Gu. 4430-4440 [doi]
- Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical ModelsChristian Weilbach, Boyan Beronov, Frank Wood, William Harvey. 4441-4451 [doi]
- Graph Coarsening with Preserved Spectral PropertiesYu Jin, Andreas Loukas, Joseph JáJá. 4452-4462 [doi]
- A Theoretical and Practical Framework for Regression and Classification from Truncated SamplesAndrew Ilyas, Emmanouil Zampetakis, Constantinos Daskalakis. 4463-4473 [doi]
- Permutation Invariant Graph Generation via Score-Based Generative ModelingChenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon. 4474-4484 [doi]
- Finite-Time Analysis of Decentralized Temporal-Difference Learning with Linear Function ApproximationJun Sun, Gang Wang, Georgios B. Giannakis, Qinmin Yang, Zaiyue Yang. 4485-4495 [doi]
- Multi-attribute Bayesian optimization with interactive preference learningRaul Astudillo, Peter I. Frazier. 4496-4507 [doi]
- On the Sample Complexity of Learning Sum-Product NetworksIshaq Aden-Ali, Hassan Ashtiani. 4508-4518 [doi]
- Tighter Theory for Local SGD on Identical and Heterogeneous DataAhmed Khaled 0001, Konstantin Mishchenko, Peter Richtárik. 4519-4529 [doi]
- Approximate Cross-validation: Guarantees for Model Assessment and SelectionAshia C. Wilson, Maximilian Kasy, Lester Mackey. 4530-4540 [doi]
- On Minimax Optimality of GANs for Robust Mean EstimationKaiwen Wu, Gavin Weiguang Ding, Ruitong Huang, Yaoliang Yu. 4541-4551 [doi]
- Auditing ML Models for Individual Bias and UnfairnessSongkai Xue, Mikhail Yurochkin, Yuekai Sun. 4552-4562 [doi]
- Stein Variational Inference for Discrete DistributionsJun Han, Fan Ding, Xianglong Liu, Lorenzo Torresani, Jian Peng, Qiang Liu. 4563-4572 [doi]
- Revisiting Stochastic ExtragradientKonstantin Mishchenko, Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Yura Malitsky. 4573-4582 [doi]
- A Framework for Sample Efficient Interval Estimation with Control VariatesShengjia Zhao, Christopher Yeh, Stefano Ermon. 4583-4592 [doi]
- Nonmyopic Gaussian Process Optimization with Macro-ActionsDmitrii Kharkovskii, Chun Kai Ling, Bryan Kian Hsiang Low. 4593-4604 [doi]