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Viewing Publication 1 - 100 from 11204

2023

Generalized Implicit Follow-The-Regularized-LeaderKeyi Chen 0001, Francesco Orabona. icml 2023: 4826-4838 [doi]

SAM operates far from home: eigenvalue regularization as a dynamical phenomenonAtish Agarwala, Yann N. Dauphin. icml 2023: 152-168 [doi]

Second-order regression models exhibit progressive sharpening to the edge of stabilityAtish Agarwala, Fabian Pedregosa, Jeffrey Pennington. icml 2023: 169-195 [doi]

SemSup-XC: Semantic Supervision for Zero and Few-shot Extreme ClassificationPranjal Aggarwal, Ameet Deshpande, Karthik R. Narasimhan. icml 2023: 228-247 [doi]

A Kernelized Stein Discrepancy for Biological SequencesAlan Nawzad Amin, Eli N. Weinstein, Debora Susan Marks. icml 2023: 718-767 [doi]

Gradient Descent Converges Linearly for Logistic Regression on Separable DataKyriakos Axiotis, Maxim Sviridenko. icml 2023: 1302-1319 [doi]

Efficient preconditioned stochastic gradient descent for estimation in latent variable modelsCharlotte Baey, Maud Delattre, Estelle Kuhn, Jean-Benoist Leger, Sarah Lemler. icml 2023: 1430-1453 [doi]

On the Functional Similarity of Robust and Non-Robust Neural RepresentationsAndrás Balogh, Márk Jelasity. icml 2023: 1614-1635 [doi]

Polyhedral Complex Extraction from ReLU Networks using Edge SubdivisionArturs Berzins. icml 2023: 2234-2244 [doi]

FLEX: an Adaptive Exploration Algorithm for Nonlinear SystemsMatthieu Blanke, Marc Lelarge. icml 2023: 2577-2591 [doi]

A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural NetworksDavid Boetius, Stefan Leue, Tobias Sutter. icml 2023: 2712-2737 [doi]

Model-agnostic Measure of Generalization DifficultyAkhilan Boopathy, Kevin Liu, Jaedong Hwang, Shu Ge, Asaad Mohammedsaleh, Ila R. Fiete. icml 2023: 2857-2884 [doi]

Stein Variational Goal Generation for adaptive Exploration in Multi-Goal Reinforcement LearningNicolas Castanet, Olivier Sigaud, Sylvain Lamprier. icml 2023: 3714-3731 [doi]

On the Statistical Benefits of Temporal Difference LearningDavid Cheikhi, Daniel Russo 0001. icml 2023: 4269-4293 [doi]

Multi-Layer Neural Networks as Trainable Ladders of Hilbert SpacesZhengdao Chen. icml 2023: 4294-4329 [doi]

Context-Aware Bayesian Network Actor-Critic Methods for Cooperative Multi-Agent Reinforcement LearningDingyang Chen, Qi Zhang 0038. icml 2023: 5327-5350 [doi]

How to address monotonicity for model risk management?Dangxing Chen, Weicheng Ye. icml 2023: 5282-5295 [doi]

Layered State Discovery for Incremental Autonomous ExplorationLiyu Chen, Andrea Tirinzoni, Alessandro Lazaric, Matteo Pirotta. icml 2023: 4953-5001 [doi]

Is Overfitting Necessary for Implicit Video Representation?Hee Min Choi, Hyoa Kang, Dokwan Oh. icml 2023: 5748-5770 [doi]

What do CNNs Learn in the First Layer and Why? A Linear Systems PerspectiveRhea Chowers, Yair Weiss. icml 2023: 6115-6139 [doi]

Distribution Free Prediction Sets for Node ClassificationJase Clarkson. icml 2023: 6268-6278 [doi]

Task-specific experimental design for treatment effect estimationBethany Connolly, Kim Moore, Tobias Schwedes, Alexander Adam, Gary Willis, Ilya Feige, Christopher Frye. icml 2023: 6384-6401 [doi]

On the Robustness of Randomized Ensembles to Adversarial PerturbationsHassan Dbouk, Naresh R. Shanbhag. icml 2023: 7303-7328 [doi]

Efficient Parametric Approximations of Neural Network Function Space DistanceNikita Dhawan, Sicong Huang, Juhan Bae, Roger Baker Grosse. icml 2023: 7795-7812 [doi]

Meta-Learning the Inductive Bias of Simple Neural CircuitsWill Dorrell, Maria Yuffa, Peter E. Latham. icml 2023: 8389-8402 [doi]

Linear Time GPs for Inferring Latent Trajectories from Neural Spike TrainsMatthew Dowling, Yuan Zhao 0004, Il Memming Park. icml 2023: 8424-8448 [doi]

A new near-linear time algorithm for k-nearest neighbor search using a compressed cover treeYury Elkin, Vitaliy Kurlin. icml 2023: 9267-9311 [doi]

Learning Perturbations to Explain Time Series PredictionsJoseph Enguehard. icml 2023: 9329-9342 [doi]

Predicting Rare Events by Shrinking Towards Proportional OddsGregory Faletto, Jacob Bien. icml 2023: 9547-9602 [doi]

Cell-Free Latent Go-ExploreQuentin Gallouédec, Emmanuel Dellandréa. icml 2023: 10571-10586 [doi]

Scaling Laws for Reward Model OveroptimizationLeo Gao, John Schulman, Jacob Hilton. icml 2023: 10835-10866 [doi]

Aligning Language Models with Preferences through f-divergence MinimizationDongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Nahyeon Ryu, Marc Dymetman. icml 2023: 11546-11583 [doi]

Conformalization of Sparse Generalized Linear ModelsEtash Kumar Guha, Eugène Ndiaye, Xiaoming Huo. icml 2023: 11871-11887 [doi]

Social learning spontaneously emerges by searching optimal heuristics with deep reinforcement learningSeungwoong Ha, Hawoong Jeong. icml 2023: 12319-12338 [doi]

Counterfactual Analysis in Dynamic Latent State ModelsMartin B. Haugh, Raghav Singal. icml 2023: 12647-12677 [doi]

Width and Depth Limits Commute in Residual NetworksSoufiane Hayou, Greg Yang. icml 2023: 12700-12723 [doi]

Functional Neural Networks: Shift invariant models for functional data with applications to EEG classificationFlorian Heinrichs, Mavin Heim, Corinna Weber. icml 2023: 12866-12881 [doi]

Decoding Layer Saliency in Language TransformersElizabeth Mary Hou, Gregory David Castañón. icml 2023: 13285-13308 [doi]

Short-lived High-volume BanditsSu Jia, Nishant Oli, Ian Anderson, Paul Duff, Andrew A. Li, R. Ravi 0001. icml 2023: 14902-14929 [doi]

Biases in Evaluation of Molecular Optimization Methods and Bias Reduction StrategiesHiroshi Kajino, Kohei Miyaguchi, Takayuki Osogami. icml 2023: 15567-15585 [doi]

Understanding Gradient Regularization in Deep Learning: Efficient Finite-Difference Computation and Implicit BiasRyo Karakida, Tomoumi Takase, Tomohiro Hayase, Kazuki Osawa. icml 2023: 15809-15827 [doi]

Regression with Sensor Data Containing Incomplete ObservationsTakayuki Katsuki, Takayuki Osogami. icml 2023: 15911-15927 [doi]

Data Representations' Study of Latent Image ManifoldsIlya Kaufman, Omri Azencot. icml 2023: 15928-15945 [doi]

The Test of Tests: A Framework for Differentially Private Hypothesis TestingZeki Kazan, Kaiyan Shi, Adam Groce, Andrew P. Bray. icml 2023: 16131-16151 [doi]

Trainability, Expressivity and Interpretability in Gated Neural ODEsTimothy Doyeon Kim, Tankut Can, Kamesh Krishnamurthy. icml 2023: 16393-16423 [doi]

Learnability and Algorithm for Continual LearningGyuhak Kim, Changnan Xiao, Tatsuya Konishi, Bing Liu 0001. icml 2023: 16877-16896 [doi]

Detecting Adversarial Directions in Deep Reinforcement Learning to Make Robust DecisionsEzgi Korkmaz, Jonah Brown-Cohen. icml 2023: 17534-17543 [doi]

Tied-Augment: Controlling Representation Similarity Improves Data AugmentationEmirhan Kurtulus, Zichao Li, Yann N. Dauphin, Ekin Dogus Cubuk. icml 2023: 17994-18007 [doi]

Emergence of Adaptive Circadian Rhythms in Deep Reinforcement LearningAqeel Labash, Florian Stelzer, Daniel Majoral, Raul Vicente Zafra. icml 2023: 18153-18170 [doi]

Hybrid Energy Based Model in the Feature Space for Out-of-Distribution DetectionMarc Lafon, Elias Ramzi, Clément Rambour, Nicolas Thome. icml 2023: 18250-18268 [doi]

Delay-Adapted Policy Optimization and Improved Regret for Adversarial MDP with Delayed Bandit FeedbackTal Lancewicki, Aviv Rosenberg 0002, Dmitry Sotnikov. icml 2023: 18482-18534 [doi]

Cluster Explanation via Polyhedral DescriptionsConnor Lawless, Oktay Günlük. icml 2023: 18652-18666 [doi]

H-Likelihood Approach to Deep Neural Networks with Temporal-Spatial Random Effects for High-Cardinality Categorical FeaturesHangbin Lee, Youngjo Lee. icml 2023: 18974-18987 [doi]

Minimum Width of Leaky-ReLU Neural Networks for Uniform Universal ApproximationLi'ang Li, Yifei Duan, Guanghua Ji, Yongqiang Cai. icml 2023: 19460-19470 [doi]

Learning Antidote Data to Individual UnfairnessPeizhao Li, Ethan Xia, Hongfu Liu. icml 2023: 20168-20181 [doi]

spred: Solving L1 Penalty with SGDZiyin Liu, Zihao Wang 0001. icml 2023: 43407-43422 [doi]

Reliable Measures of Spread in High Dimensional Latent SpacesAnna C. Marbut, Katy McKinney-Bock, Travis J. Wheeler. icml 2023: 23871-23885 [doi]

Evaluating Unsupervised Denoising Requires Unsupervised MetricsAdria Marcos-Morales, Matan Leibovich, Sreyas Mohan, Joshua Lawrence Vincent, Piyush Haluai, Mai Tan, Peter A. Crozier, Carlos Fernandez-Granda. icml 2023: 23937-23957 [doi]

Computational Asymmetries in Robust ClassificationSamuele Marro, Michele Lombardi 0001. icml 2023: 24082-24138 [doi]

Nonlinear Advantage: Trained Networks Might Not Be As Complex as You ThinkChristian H. X. Ali Mehmeti-Göpel, Jan Disselhoff. icml 2023: 529-546 [doi]

Training Deep Surrogate Models with Large Scale Online LearningLucas Thibaut Meyer, Marc Schouler, Robert Alexander Caulk, Alejandro Ribés, Bruno Raffin. icml 2023: 24614-24630 [doi]

Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learningThomas Miconi. icml 2023: 24756-24774 [doi]

An Information-Theoretic Analysis of Nonstationary Bandit LearningSeungki Min, Daniel Russo 0001. icml 2023: 24831-24849 [doi]

Directed Chain Generative Adversarial NetworksMing Min, Ruimeng Hu, Tomoyuki Ichiba. icml 2023: 24812-24830 [doi]

Input uncertainty propagation through trained neural networksPaul Monchot, Loic Coquelin, Sébastien Julien Petit, Sébastien Marmin, Erwan Le Pennec, Nicolas Fischer. icml 2023: 25140-25173 [doi]

Achieving High Accuracy with PINNs via Energy Natural Gradient DescentJohannes Müller, Marius Zeinhofer. icml 2023: 25471-25485 [doi]

Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive EstimationIlan Naiman, Nimrod Berman, Omri Azencot. icml 2023: 25694-25717 [doi]

Towards Understanding Ensemble Distillation in Federated LearningSejun Park, Kihun Hong, Ganguk Hwang. icml 2023: 27132-27187 [doi]

Model-based Reinforcement Learning with Scalable Composite Policy Gradient EstimatorsPaavo Parmas, Takuma Seno, Yuma Aoki. icml 2023: 27346-27377 [doi]

Stochastic Gradient Descent-Induced Drift of Representation in a Two-Layer Neural NetworkFarhad Pashakhanloo, Alexei Koulakov. icml 2023: 27401-27419 [doi]

Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNsSaro Passaro, C. Lawrence Zitnick. icml 2023: 27420-27438 [doi]

How Jellyfish Characterise Alternating Group Equivariant Neural NetworksEdward Pearce-Crump. icml 2023: 27483-27495 [doi]

Brauer's Group Equivariant Neural NetworksEdward Pearce-Crump. icml 2023: 27461-27482 [doi]

Linear CNNs Discover the Statistical Structure of the Dataset Using Only the Most Dominant FrequenciesHannah Pinson, Joeri Lenaerts, Vincent Ginis. icml 2023: 27876-27906 [doi]

Universal Physics-Informed Neural Networks: Symbolic Differential Operator Discovery with Sparse DataLena Podina, Brydon Eastman, Mohammad Kohandel. icml 2023: 27948-27956 [doi]

Spurious Valleys and Clustering Behavior of Neural NetworksSamuele Pollaci. icml 2023: 28079-28099 [doi]

Intrinsic Sliced Wasserstein Distances for Comparing Collections of Probability Distributions on Manifolds and GraphsRaif M. Rustamov, Subhabrata Majumdar. icml 2023: 29388-29415 [doi]

Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy RegimesSeyed Amir Hossein Saberi, Amir Najafi 0003, Abolfazl S. Motahari, Babak H. Khalaj. icml 2023: 29514-29541 [doi]

Existence and Estimation of Critical Batch Size for Training Generative Adversarial Networks with Two Time-Scale Update RuleNaoki Sato, Hideaki Iiduka. icml 2023: 30080-30104 [doi]

Gibbsian Polar Slice SamplingPhilip Schär, Michael Habeck, Daniel Rudolf. icml 2023: 30204-30223 [doi]

Neural Markov Jump ProcessesPatrick Seifner, Ramsés J. Sánchez. icml 2023: 30523-30552 [doi]

Bayesian online change point detection with Hilbert space approximate Student-t processJeremy Sellier, Petros Dellaportas. icml 2023: 30553-30569 [doi]

Improved Learning-Augmented Algorithms for the Multi-Option Ski Rental Problem via Best-Possible Competitive AnalysisYongho Shin, Changyeol Lee, Gukryeol Lee, Hyung-Chan An. icml 2023: 31539-31561 [doi]

Quantitative Universal Approximation Bounds for Deep Belief NetworksJulian Sieber, Johann Gehringer. icml 2023: 31773-31787 [doi]

On the Stepwise Nature of Self-Supervised LearningJames B. Simon, Maksis Knutins, Ziyin Liu, Daniel Geisz, Abraham J. Fetterman, Joshua Albrecht. icml 2023: 31852-31876 [doi]

Importance Weighted Expectation-Maximization for Protein Sequence DesignZhenqiao Song, Lei Li 0005. icml 2023: 32349-32364 [doi]

Are labels informative in semi-supervised learning? Estimating and leveraging the missing-data mechanismAude Sportisse, Hugo Schmutz, Olivier Humbert, Charles Bouveyron, Pierre-Alexandre Mattei. icml 2023: 32521-32539 [doi]

Proximal Causal Learning of Conditional Average Treatment EffectsErik Sverdrup, Yifan Cui 0001. icml 2023: 33285-33298 [doi]

Von Mises Mixture Distributions for Molecular Conformation GenerationKirk Swanson, Jake Lawrence Williams, Eric M. Jonas. icml 2023: 33319-33342 [doi]

Optimal randomized multilevel Monte Carlo for repeatedly nested expectationsYasa Syed, Guanyang Wang. icml 2023: 33343-33364 [doi]

PWSHAP: A Path-Wise Explanation Model for Targeted VariablesLucile Ter-Minassian, Oscar Clivio, Karla DiazOrdaz, Robin J. Evans, Christopher C. Holmes. icml 2023: 34054-34089 [doi]

On the Estimation of Gaussian Mixture Copula ModelsAshutosh Tewari. icml 2023: 34090-34104 [doi]

Causal Isotonic Calibration for Heterogeneous Treatment EffectsLars van der Laan, Ernesto Ulloa-Pérez, Marco Carone, Alex Luedtke. icml 2023: 34831-34854 [doi]

Low-Variance Gradient Estimation in Unrolled Computation Graphs with ES-SinglePaul Vicol. icml 2023: 35084-35119 [doi]

Arithmetic Sampling: Parallel Diverse Decoding for Large Language ModelsLuke Vilnis, Yury Zemlyanskiy, Patrick Murray, Alexandre Tachard Passos, Sumit Sanghai. icml 2023: 35120-35136 [doi]

A Critical View of Vision-Based Long-Term Dynamics Prediction Under Environment MisalignmentHanchen Xie, Jiageng Zhu, Mahyar Khayatkhoei, Jiazhi Li, Mohamed E. Hussein 0001, Wael AbdAlmageed. icml 2023: 38258-38271 [doi]

Proper Scoring Rules for Survival AnalysisHiroki Yanagisawa. icml 2023: 39165-39182 [doi]

Coordinate Descent Methods for Fractional MinimizationGanzhao Yuan. icml 2023: 40488-40518 [doi]

Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty NoiseShiwei Zeng, Jie Shen 0005. icml 2023: 40719-40748 [doi]

Horizon-Free and Variance-Dependent Reinforcement Learning for Latent Markov Decision ProcessesRunlong Zhou, Ruosong Wang, Simon Shaolei Du. icml 2023: 42698-42723 [doi]

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2023

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