Table of Contents

• Mutation-driven follow the regularized leader for last-iterate convergence in zero-sum gamesKenshi Abe, Mitsuki Sakamoto, Atsushi Iwasaki. 1-10 [doi]
• NeuroBE: Escalating neural network approximations of Bucket EliminationSakshi Agarwal, Kalev Kask, Alex Ihler, Rina Dechter. 11-21 [doi]
• Regret guarantees for model-based reinforcement learning with long-term average constraintsMridul Agarwal, Qinbo Bai, Vaneet Aggarwal. 22-31 [doi]
• GNN2GNN: Graph neural networks to generate neural networksAndrea Agiollo, Andrea Omicini. 32-42 [doi]
• Neuro-symbolic entropy regularizationKareem Ahmed, Eric Wang, Kai-Wei Chang, Guy Van den Broeck. 43-53 [doi]
• Non-parametric inference of relational dependenceRagib Ahsan, Zahra Fatemi, David Arbour, Elena Zheleva. 54-63 [doi]
• Data dependent randomized smoothingMotasem Alfarra, Adel Bibi, Philip H. S. Torr, Bernard Ghanem. 64-74 [doi]
• Multi-winner approval voting goes epistemicTahar Allouche, Jérôme Lang, Florian Yger. 75-84 [doi]
• Inductive synthesis of finite-state controllers for POMDPsRoman Andriushchenko, Milan Ceska 0002, Sebastian Junges, Joost-Pieter Katoen. 85-95 [doi]
• Discovery of extended summary graphs in time seriesCharles K. Assaad, Emilie Devijver, Éric Gaussier. 96-106 [doi]
• Asymmetric DQN for partially observable reinforcement learningAndrea Baisero, Brett Daley, Christopher Amato. 107-117 [doi]
• Physics guided neural networks for spatio-temporal super-resolution of turbulent flowsTianshu Bao, Shengyu Chen, Taylor T. Johnson, Peyman Givi, Shervin Sammak, Xiaowei Jia. 118-128 [doi]
• Byzantine-tolerant distributed multiclass sparse linear discriminant analysisYajie Bao, Weidong Liu 0005, Xiaojun Mao, Weijia Xiong. 129-138 [doi]
• Equilibrium aggregation: encoding sets via optimizationSergey Bartunov, Fabian B. Fuchs, Timothy P. Lillicrap. 139-149 [doi]
• Empirical bayes approach to truth discovery problemsTsviel Ben Shabat, Reshef Meir, David Azriel. 150-158 [doi]
• On early extinction and the effect of travelling in the SIR modelPetra Berenbrink, Colin Cooper, Cristina Gava, David Kohan Marzagão, Frederik Mallmann-Trenn, Tomasz Radzik. 159-169 [doi]
• Learning soft interventions in complex equilibrium systemsMichel Besserve, Bernhard Schölkopf. 170-180 [doi]
• Identifying near-optimal decisions in linear-in-parameter bandit models with continuous decision setsSanjay P. Bhat, Chaitanya Amballa. 181-190 [doi]
• Offline change detection under contaminationSujay Bhatt, Guanhua Fang, Ping Li 0001. 191-201 [doi]
• On testability of the front-door model via Verma constraintsRohit Bhattacharya, Razieh Nabi. 202-212 [doi]
• Robustness of model predictions under extensionTineke Blom, Joris M. Mooij. 213-222 [doi]
• Information theoretic approach to detect collusion in multi-agent gamesTrevor Bonjour, Vaneet Aggarwal, Bharat K. Bhargava. 223-232 [doi]
• Lifting in multi-agent systems under uncertaintyTanya Braun, Marcel Gehrke, Florian Lau, Ralf Möller 0001. 233-243 [doi]
• On-the-fly adaptation of patrolling strategies in changing environmentsTomás Brázdil, David Klaska, Antonín Kucera 0001, Vít Musil, Petr Novotný 0001, Vojtech Rehák. 244-254 [doi]
• On the inductive bias of neural networks for learning read-once DNFsIdo Bronstein, Alon Brutzkus, Amir Globerson. 255-265 [doi]
• AUTM flow: atomic unrestricted time machine for monotonic normalizing flowsDifeng Cai, Yuliang Ji, Huan He, Qiang Ye, Yuanzhe Xi. 266-274 [doi]
• Active approximately metric-fair learningYiting Cao, Chao Lan. 275-285 [doi]
• Capturing actionable dynamics with structured latent ordinary differential equationsPaidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao. 286-295 [doi]
• Privacy-aware compression for federated data analysisKamalika Chaudhuri, Chuan Guo, Mike Rabbat. 296-306 [doi]
• The optimal noise in noise-contrastive learning is not what you thinkOmar Chehab, Alexandre Gramfort, Aapo Hyvärinen. 307-316 [doi]
• A competitive analysis of online failure-aware assignmentMengjing Chen, Pingzhong Tang, Zihe Wang 0001, Shenke Xiao, Xiwang Yang. 317-325 [doi]
• Stackmix: a complementary mix algorithmJohn Chen, Samarth Sinha, Anastasios Kyrillidis. 326-335 [doi]
• Knowledge representation combining quaternion path integration and depth-wise atrous circular convolutionXinyuan Chen, Zhongmei Zhou, Meichun Gao, Daya Shi, Mohd Nizam Husen. 336-345 [doi]
• Sublinear time algorithms for greedy selection in high dimensionsQi Chen, Kai Liu, Ruilong Yao, Hu Ding. 346-356 [doi]
• Shoring up the foundations: fusing model embeddings and weak supervisionMayee F. Chen, Daniel Y. Fu, Dyah Adila, Michael Zhang, Frederic Sala, Kayvon Fatahalian, Christopher Ré. 357-367 [doi]
• On the definition and computation of causal treewidthYizuo Chen, Adnan Darwiche. 368-377 [doi]
• Offline reinforcement learning under value and density-ratio realizability: The power of gapsJinglin Chen, Nan Jiang 0008. 378-388 [doi]
• Greedy modality selection via approximate submodular maximizationRunxiang Cheng, Gargi Balasubramaniam, Yifei He, Yao-Hung Hubert Tsai, Han Zhao 0002. 389-399 [doi]
• Feature selection for discovering distributional treatment effect modifiersYoichi Chikahara, Makoto Yamada, Hisashi Kashima. 400-410 [doi]
• Combating the instability of mutual information-based losses via regularizationKwangHee Choi, Siyeong Lee. 411-421 [doi]
• A geometric method for improved uncertainty estimation in real-timeGabriella Chouraqui, Liron Cohen 0001, Gil Einziger, Liel Leman. 422-432 [doi]
• Cyclic test time augmentation with entropy weight methodSewhan Chun, Jae Young Lee, Junmo Kim. 433-442 [doi]
• Greedy equivalence search in the presence of latent confoundersTom Claassen, Ioan Gabriel Bucur. 443-452 [doi]
• Counterfactual inference of second OpinionsNina L. Corvelo Benz, Manuel Gomez-Rodriguez. 453-463 [doi]
• Variational message passing neural network for Maximum-A-Posteriori (MAP) inferenceZijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji. 464-474 [doi]
• On provably robust meta-Bayesian optimizationZhongxiang Dai, Yizhou Chen, Haibin Yu, Bryan Kian Hsiang Low, Patrick Jaillet. 475-485 [doi]
• Individual fairness in feature-based pricing for monopoly marketsShantanu Das, Swapnil Dhamal, Ganesh Ghalme, Shweta Jain 0002, Sujit Gujar. 486-495 [doi]
• Faster non-convex federated learning via global and local momentumRudrajit Das, Anish Acharya, Abolfazl Hashemi, Sujay Sanghavi, Inderjit S. Dhillon, Ufuk Topcu. 496-506 [doi]
• Multi-objective Bayesian optimization over high-dimensional search spacesSamuel Daulton, David Eriksson, Maximilian Balandat, Eytan Bakshy. 507-517 [doi]
• Bayesian structure learning with generative flow networksTristan Deleu, António Góis, Chris Emezue, Mansi Rankawat, Simon Lacoste-Julien, Stefan Bauer, Yoshua Bengio. 518-528 [doi]
• Bayesian spillover graphs for dynamic networksGrace Deng, David S. Matteson. 529-538 [doi]
• Multiclass classification for Hawkes processesChristophe Denis, Charlotte Dion-Blanc, Laure Sansonnet. 539-547 [doi]
• Quantification of Credal Uncertainty in Machine Learning: A Critical Analysis and Empirical ComparisonEyke Hüllermeier, Sébastien Destercke, Mohammad Hossein Shaker. 548-557 [doi]
• Balancing adaptability and non-exploitability in repeated gamesAnthony DiGiovanni, Ambuj Tewari. 559-568 [doi]
• Variational- and metric-based deep latent space for out-of-distribution detectionOr Dinari, Oren Freifeld. 569-578 [doi]
• Revisiting DP-Means: fast scalable algorithms via parallelism and delayed cluster creationOr Dinari, Oren Freifeld. 579-588 [doi]
• X-MEN: guaranteed XOR-maximum entropy constrained inverse reinforcement learningFan Ding, Yexiang Xue. 589-598 [doi]
• Improving sign-random-projection via count sketchPunit Pankaj Dubey, Bhisham Dev Verma, Rameshwar Pratap, Keegan Kang. 599-609 [doi]
• ResIST: Layer-wise decomposition of ResNets for distributed trainingChen Dun, Cameron R. Wolfe, Christopher M. Jermaine, Anastasios Kyrillidis. 610-620 [doi]
• Learning explainable templated graphical modelsVarun Embar, Sriram Srinivasan 0004, Lise Getoor. 621-630 [doi]
• SENTINEL: taming uncertainty with ensemble based distributional reinforcement learningHannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis. 631-640 [doi]
• Temporal abstractions-augmented temporally contrastive learning: An alternative to the Laplacian in RLAkram Erraqabi, Marlos C. Machado, Mingde Zhao, Sainbayar Sukhbaatar, Alessandro Lazaric, Ludovic Denoyer, Yoshua Bengio. 641-651 [doi]
• Implicit kernel meta-learning using kernel integral formsJohn Isak Texas Falk, Carlo Ciliberto, Massimiliano Pontil. 652-662 [doi]
• Self-distribution distillation: efficient uncertainty estimationYassir Fathullah, Mark J. F. Gales. 663-673 [doi]
• Sequential algorithmic modification with test data reuseJean Feng, Gene Pennello, Nicholas Petrick, Berkman Sahiner, Romain Pirracchio, Alexej Gossmann. 674-684 [doi]
• Estimating transfer entropy under long ranged dependenciesSahil Garg, Umang Gupta, Yu Chen, Syamantak Datta Gupta, Yeshaya Adler, Anderson Schneider, Yuriy Nevmyvaka. 685-695 [doi]
• Mitigating statistical bias within differentially private synthetic dataSahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes. 696-705 [doi]
• Neural-progressive hedging: Enforcing constraints in reinforcement learning with stochastic programmingSupriyo Ghosh, Laura Wynter, Shiau Hong Lim, Duc Thien Nguyen. 707-717 [doi]
• Do Bayesian variational autoencoders know what they don't know?Misha Glazunov, Apostolis Zarras. 718-727 [doi]
• Robust expected information gain for optimal Bayesian experimental design using ambiguity setsJinwoo Go, Tobin Isaac. 728-737 [doi]
• Efficient and transferable adversarial examples from bayesian neural networksMartin Gubri, Maxime Cordy, Mike Papadakis, Yves Le Traon, Koushik Sen. 738-748 [doi]
• Learning a neural Pareto manifold extractor with constraintsSoumyajit Gupta, Gurpreet Singh, Raghu Bollapragada, Matthew Lease. 749-758 [doi]
• Modeling extremes with d-max-decreasing neural networksAli-Hasan, Khalil Elkhalil, Yuting Ng, João M. Pereira 0002, Sina Farsiu, Jose H. Blanchet, Vahid Tarokh. 759-768 [doi]
• Generalizing off-policy learning under sample selection biasTobias Hatt, Daniel Tschernutter, Stefan Feuerriegel. 769-779 [doi]
• Reinforcement learning in many-agent settings under partial observabilityKeyang He, Prashant Doshi, Bikramjit Banerjee. 780-789 [doi]
• Variational multiple shooting for Bayesian ODEs with Gaussian processesPashupati Hegde, Çagatay Yildiz, Harri Lähdesmäki, Samuel Kaski, Markus Heinonen. 790-799 [doi]
• Learning sparse representations of preferences within Choquet expected utility theoryMargot Herin, Patrice Perny, Nataliya Sokolovska. 800-810 [doi]
• Quadratic metric elicitation for fairness and beyondGaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan, Oluwasanmi Koyejo. 811-821 [doi]
• Fast predictive uncertainty for classification with Bayesian deep networksMarius Hobbhahn, Agustinus Kristiadi, Philipp Hennig. 822-832 [doi]
• CIGMO: Categorical invariant representations in a deep generative frameworkHaruo Hosoya. 833-843 [doi]
• Near-optimal Thompson sampling-based algorithms for differentially private stochastic banditsBingshan Hu, Nidhi Hegde 0001. 844-852 [doi]
• Uncertainty-aware pseudo-labeling for quantum calculationsKexin Huang, Vishnu Sresht, Brajesh K. Rai, Mykola Bordyuh. 853-862 [doi]
• A mutually exciting latent space Hawkes process model for continuous-time networksZhipeng Huang 0011, Hadeel Soliman, Subhadeep Paul, Kevin S. Xu 0001. 863-873 [doi]
• Binary independent component analysis: a non-stationarity-based approachAntti Hyttinen, Vitória Barin Pacela, Aapo Hyvärinen. 874-884 [doi]
• Balancing utility and scalability in metric differential privacyJacob Imola, Shiva Prasad Kasiviswanathan, Stephen White, Abhinav Aggarwal, Nathanael Teissier. 885-894 [doi]
• Towards painless policy optimization for constrained MDPsArushi Jain, Sharan Vaswani, Reza Babanezhad, Csaba Szepesváari, Doina Precup. 895-905 [doi]
• Fedvarp: Tackling the variance due to partial client participation in federated learningDivyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi. 906-916 [doi]
• Orthogonal Gromov-Wasserstein discrepancy with efficient lower boundHongwei Jin, Zishun Yu, Xinhua Zhang. 917-927 [doi]
• If you've trained one you've trained them all: inter-architecture similarity increases with robustnessHaydn T. Jones, Jacob M. Springer, Garrett T. Kenyon, Juston S. Moore. 928-937 [doi]
• Decision-theoretic planning with communication in open multiagent systemsAnirudh Kakarlapudi, Gayathri Anil, Adam Eck, Prashant Doshi, Leen-Kiat Soh. 938-948 [doi]
• Optimal control of partially observable Markov decision processes with finite linear temporal logic constraintsKrishna Chaitanya Kalagarla, Kartik Dhruva, Dongming Shen, Rahul Jain 0002, Ashutosh Nayyar, Pierluigi Nuzzo. 949-958 [doi]
• Test for non-negligible adverse shiftsVathy M. Kamulete. 959-968 [doi]
• Improved feature importance computation for tree models based on the Banzhaf valueAdam Karczmarz, Tomasz Michalak, Anish Mukherjee 0001, Piotr Sankowski, Piotr Wygocki. 969-979 [doi]
• Dynamic relocation in ridesharing via fixpoint constructionIan A. Kash, Zhongkai Wen, Lenore D. Zuck. 980-989 [doi]
• Restless and uncertain: Robust policies for restless bandits via deep multi-agent reinforcement learningJackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe. 990-1000 [doi]
• Combinatorial Bayesian optimization with random mapping functions to convex polytopesJungtaek Kim 0001, Seungjin Choi, Minsu Cho. 1001-1011 [doi]
• On the effectiveness of adversarial training against common corruptionsKlim Kireev, Maksym Andriushchenko, Nicolas Flammarion. 1012-1021 [doi]
• Revisiting the general identifiability problemYaroslav Kivva, Ehsan Mokhtarian, Jalal Etesami, Negar Kiyavash. 1022-1030 [doi]
• Hitting times for continuous-time imprecise-Markov chainsThomas Krak. 1031-1040 [doi]
• Calibrated ensembles can mitigate accuracy tradeoffs under distribution shiftAnanya Kumar, Tengyu Ma 0001, Percy Liang, Aditi Raghunathan. 1041-1051 [doi]
• Greedy relaxations of the sparsest permutation algorithmWai-Yin Lam, Bryan Andrews, Joseph D. Ramsey. 1052-1062 [doi]
• Interpolating between sampling and variational inference with infinite stochastic mixturesRichard D. Lange, Ari S. Benjamin, Ralf M. Haefner, Xaq Pitkow. 1063-1073 [doi]
• Systematized event-aware learning for multi-object trackingHyemin Lee, Daijin Kim 0001. 1074-1084 [doi]
• Fixing the Bethe approximation: How structural modifications in a graph improve belief propagationHarald Leisenberger, Franz Pernkopf, Christian Knoll 0002. 1085-1095 [doi]
• Recursive Monte Carlo and variational inference with auxiliary variablesAlexander K. Lew, Marco Cusumano-Towner, Vikash K. Mansinghka. 1096-1106 [doi]
• Solving structured hierarchical games using differential backward inductionZun Li, Feiran Jia, Aditya Mate, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Yevgeniy Vorobeychik. 1107-1117 [doi]
• PDQ-Net: Deep probabilistic dual quaternion network for absolute pose regression on SE(3)Wenjie Li, Wasif Naeem, Jia Liu 0008, Dequan Zheng, Wei Hao, Lijun Chen. 1118-1127 [doi]
• Accelerating training of batch normalization: A manifold perspectiveMingyang Yi. 1128-1137 [doi]
• Deep Dirichlet process mixture modelsNaiqi Li, Wenjie Li 0008, Yong Jiang 0001, Shu-Tao Xia. 1138-1147 [doi]
• Proportional allocation of indivisible resources under ordinal and uncertain preferencesZihao Li, Xiaohui Bei, Zhenzhen Yan. 1148-1157 [doi]
• Efficient resource allocation with fairness constraints in restless multi-armed banditsDexun Li, Pradeep Varakantham. 1158-1167 [doi]
• A label efficient two-sample testWeizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha. 1168-1177 [doi]
• ∞-Bounds of the MLE in the BTL Model under General Comparison GraphsWanshan Li, Shamindra Shrotriya, Alessandro Rinaldo. 1178-1187 [doi]
• AdaCat: Adaptive categorical discretization for autoregressive modelsQiyang Li, Ajay Jain, Pieter Abbeel. 1188-1198 [doi]
• Laplace approximated Gaussian process state-space modelsJakob Lindinger, Barbara Rakitsch, Christoph Lippert. 1199-1209 [doi]
• Dimension reduction for high-dimensional small counts with KL divergenceYurong Ling, Jing-Hao Xue. 1210-1220 [doi]
• Federated online clustering of banditsXutong Liu 0002, Haoru Zhao, Tong Yu 0001, Shuai Li, John C. S. Lui. 1221-1231 [doi]
• PathFlow: A normalizing flow generator that finds transition pathsTianyi Liu, Weihao Gao, Zhirui Wang, Chong Wang. 1232-1242 [doi]
• SASH: Efficient secure aggregation based on SHPRG for federated learningZizhen Liu, Si Chen, Jing Ye, Junfeng Fan, Huawei Li, Xiaowei Li. 1243-1252 [doi]
• Offline policy optimization with eligible actionsYao Liu 0009, Yannis Flet-Berliac, Emma Brunskill. 1253-1263 [doi]
• Data poisoning attacks on off-policy policy evaluation methodsElita A. Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin, Himabindu Lakkaraju. 1264-1274 [doi]
• Nonparametric exponential family graph embeddings for multiple representation learningChien Lu, Jaakko Peltonen, Timo Nummenmaa, Jyrki Nummenmaa. 1275-1285 [doi]
• Local calibration: metrics and recalibrationRachel Luo, Aadyot Bhatnagar, Yu Bai, Shengjia Zhao, Huan Wang, Caiming Xiong, Silvio Savarese, Stefano Ermon, Edward Schmerling, Marco Pavone. 1286-1295 [doi]
• Data sampling affects the complexity of online SGD over dependent dataShaocong Ma, Ziyi Chen 0002, Yi Zhou 0017, Kaiyi Ji, Yingbin Liang. 1296-1305 [doi]
• Low-precision arithmetic for fast Gaussian processesWesley J. Maddox, Andres Potapczynski, Andrew Gordon Wilson. 1306-1316 [doi]
• Perturbation type categorization for multiple adversarial perturbation robustnessPratyush Maini, Xinyun Chen, Bo Li, Dawn Song. 1317-1327 [doi]
• A causal bandit approach to learning good atomic interventions in presence of unobserved confoundersAurghya Maiti, Vineet Nair, Gaurav Sinha. 1328-1338 [doi]
• Case-based off-policy evaluation using prototype learningAnton Matsson, Fredrik D. Johansson. 1339-1349 [doi]
• Multistate analysis with infinite mixtures of Markov chainsLucas Maystre, Tiffany Wu, Roberto Sanchis-Ojeda, Tony Jebara. 1350-1359 [doi]
• Forget-me-not! Contrastive critics for mitigating posterior collapseSachit Menon, David Blei, Carl Vondrick. 1360-1370 [doi]
• Can mean field control (mfc) approximate cooperative multi agent reinforcement learning (marl) with non-uniform interaction?Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri. 1371-1380 [doi]
• Monotonicity regularization: Improved penalties and novel applications to disentangled representation learning and robust classificationJoao Monteiro, Mohamed Osama Ahmed, Hossein Hajimirsadeghi, Greg Mori. 1381-1391 [doi]
• Set-valued prediction in hierarchical classification with constrained representation complexityThomas Mortier, Eyke Hüllermeier, Krzysztof Dembczynski, Willem Waegeman. 1392-1401 [doi]
• Safety aware changepoint detection for piecewise i.i.d. banditsSubhojyoti Mukherjee. 1402-1412 [doi]
• ReVar: Strengthening policy evaluation via reduced variance samplingSubhojyoti Mukherjee, Josiah P. Hanna, Robert D. Nowak. 1413-1422 [doi]
• Probabilistic surrogate networks for simulators with unbounded randomnessAndreas Munk, Berend Zwartsenberg, Adam Scibior, Atilim Günes Baydin, Andrew Stewart, Goran Fernlund, Anoush Poursartip, Frank Wood. 1423-1433 [doi]
• Data augmentation in Bayesian neural networks and the cold posterior effectSeth Nabarro, Stoil Ganev, Adrià Garriga-Alonso, Vincent Fortuin, Mark van der Wilk, Laurence Aitchison. 1434-1444 [doi]
• Semiparametric causal sufficient dimension reduction of multidimensional treatmentsRazieh Nabi, Todd McNutt, Ilya Shpitser. 1445-1455 [doi]
• Partially adaptive regularized multiple regression analysis for estimating linear causal effectsHisayoshi Nanmo, Manabu Kuroki. 1456-1465 [doi]
• Efficient learning of sparse and decomposable PDEs using random projectionMd. Nasim, Xinghang Zhang, Anter El-Azab, Yexiang Xue. 1466-1476 [doi]
• Linearizing contextual bandits with latent state dynamicsElliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf 0001, Pascal Poupart. 1477-1487 [doi]
• CounteRGAN: Generating counterfactuals for real-time recourse and interpretability using residual GANsDaniel Nemirovsky, Nicolas Thiebaut, Ye Xu, Abhishek Gupta. 1488-1497 [doi]
• Robust Bayesian recourseTuan-Duy H. Nguyen, Ngoc Bui, Duy Nguyen, Man-Chung Yue, Viet Anh Nguyen. 1498-1508 [doi]
• Efficient and accurate top-k recovery from choice dataDuc Nguyen. 1509-1518 [doi]
• Cycle class consistency with distributional optimal transport and knowledge distillation for unsupervised domain adaptationTuan Nguyen 0004, Van Nguyen, Trung Le, He Zhao 0001, Quan Hung Tran, Dinh Q. Phung. 1519-1529 [doi]
• Ordinal causal discoveryYang Ni, Bani K. Mallick. 1530-1540 [doi]
• An explore-then-commit algorithm for submodular maximization under full-bandit feedbackGuanyu Nie, Mridul Agarwal, Abhishek Kumar Umrawal, Vaneet Aggarwal, Christopher John Quinn. 1541-1551 [doi]
• Evaluating high-order predictive distributions in deep learningIan Osband, Zheng Wen, Seyed Mohammad Asghari, Vikranth Dwaracherla, Xiuyuan Lu, Benjamin Van Roy. 1552-1560 [doi]
• Understanding and mitigating the limitations of prioritized experience replayYangchen Pan, Jincheng Mei, Amir Massoud Farahmand, Martha White, Hengshuai Yao, Mohsen Rohani, Jun Luo 0009. 1561-1571 [doi]
• Robust learning of tractable probabilistic modelsRohith Peddi, Tahrima Rahman, Vibhav Gogate. 1572-1581 [doi]
• Attribution of predictive uncertainties in classification modelsIker Perez, Piotr Skalski, Alec Barns-Graham, Jason Wong, David Sutton. 1582-1591 [doi]
• Learning large Bayesian networks with expert constraintsVaidyanathan Peruvemba Ramaswamy, Stefan Szeider. 1592-1601 [doi]
• AND/OR branch-and-bound for computational protein design optimizing KBobak Pezeshki, Radu Marinescu 0002, Alexander T. Ihler, Rina Dechter. 1602-1612 [doi]
• Identifiability of sparse causal effects using instrumental variablesNiklas Pfister, Jonas Peters. 1613-1622 [doi]
• Bayesian quantile and expectile optimisationVictor Picheny, Henry B. Moss, Léeonard Torossian, Nicolas Durrande. 1623-1633 [doi]
• Using hierarchies to efficiently combine evidence with Dempster's rule of combinationDaira Pinto Prieto, Ronald de Haan. 1634-1643 [doi]
• Voronoi density estimator for high-dimensional data: Computation, compactification and convergenceVladislav Polianskii, Giovanni Luca Marchetti, Alexander Kravberg, Anastasiia Varava, Florian T. Pokorny, Danica Kragic. 1644-1653 [doi]
• Clustering a union of linear subspaces via matrix factorization and innovation searchMostafa Rahmani. 1654-1664 [doi]
• Learning in Markov games: Can we exploit a general-sum opponent?Giorgia Ramponi, Marcello Restelli. 1665-1675 [doi]
• Expectation programming: Adapting probabilistic programming systems to estimate expectations efficientlyTim Reichelt, Adam Golinski, Luke Ong, Tom Rainforth. 1676-1685 [doi]
• A free lunch from the noise: Provable and practical exploration for representation learningTongzheng Ren, Tianjun Zhang, Csaba Szepesvári, Bo Dai. 1686-1696 [doi]
• Quantum perceptron revisited: Computational-statistical tradeoffsMathieu Roget, Giuseppe Di Molfetta, Hachem Kadri. 1697-1706 [doi]
• Resolving label uncertainty with implicit posterior modelsEsther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic. 1707-1717 [doi]
• Feature learning and random features in standard finite-width convolutional neural networks: An empirical studyMaxim Samarin, Volker Roth 0001, David Belius. 1718-1727 [doi]
• Robust identifiability in linear structural equation models of causal inferenceKarthik Abinav Sankararaman, Anand Louis, Navin Goyal. 1728-1737 [doi]
• How unfair is private learning?Amartya Sanyal, Yaxi Hu, Fanny Yang. 1738-1748 [doi]
• Probabilistic spatial transformer networksPola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg. 1749-1759 [doi]
• Learning functions on multiple sets using multi-set transformersKira A. Selby, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh, Pascal Poupart. 1760-1770 [doi]
• SymNet 2.0: Effectively handling Non-Fluents and Actions in Generalized Neural Policies for RDDL Relational MDPsVishal Sharma, Daman Arora, Florian Geißer, Mausam, Parag Singla. 1771-1781 [doi]
• Reframed GES with a neural conditional dependence measureXinwei Shen 0002, Shengyu Zhu 0001, Jiji Zhang, Shoubo Hu, Zhitang Chen. 1782-1791 [doi]
• Conditional simulation using diffusion Schrödinger bridgesYuyang Shi 0002, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet. 1792-1802 [doi]
• Neural ensemble search via Bayesian samplingYao Shu, Yizhou Chen, Zhongxiang Dai, Bryan Kian Hsiang Low. 1803-1812 [doi]
• Shifted compression framework: generalizations and improvementsEgor Shulgin, Peter Richtárik. 1813-1823 [doi]
• PAC-Bayesian domain adaptation bounds for multiclass learnersAnthony Sicilia, Katherine Atwell, Malihe Alikhani, Seong Jae Hwang. 1824-1834 [doi]
• VQ-Flows: Vector quantized local normalizing flowsSahil Sidheekh, Chris B. Dock, Tushar Jain, Radu V. Balan, Maneesh Kumar Singh 0001. 1835-1845 [doi]
• Enhanced adaptive optics control with image to image translationJeffrey Smith, Jesse Cranney, Charles Gretton, Damien Gratadour. 1846-1856 [doi]
• Fast inference and transfer of compositional task structures for few-shot task generalizationSungryull Sohn, Hyunjae Woo, Jongwook Choi, Lyubing Qiang, Izzeddin Gur, Aleksandra Faust, Honglak Lee. 1857-1865 [doi]
• Mutual information based Bayesian graph neural network for few-shot learningKaiyu Song, Kun Yue, Liang Duan, Mingze Yang, Angsheng Li. 1866-1875 [doi]
• SMT-based weighted model integration with structure awarenessGiuseppe Spallitta, Gabriele Masina, Paolo Morettin, Andrea Passerini, Roberto Sebastiani. 1876-1885 [doi]
• A robustness test for estimating total effects with covariate adjustmentZehao Su, Leonard Henckel. 1886-1895 [doi]
• Simplified and unified analysis of various learning problems by reduction to Multiple-Instance LearningDaiki Suehiro, Eiji Takimoto. 1896-1906 [doi]
• Marginal MAP estimation for inverse RL under occlusion with observer noisePrasanth Sengadu Suresh, Prashant Doshi. 1907-1916 [doi]
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