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NeurIPS 2023: all accepted papers

3,540 papers · page 34 of 36 · the most cited first · ← NeurIPS 2023

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  1. One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models ↗Ba-Hien Tran, Giulio Franzese, Pietro Michiardi A et al.
  2. Online (Multinomial) Logistic Bandit: Improved Regret and Constant Computation Cost ↗Yu-Jie Zhang, Masashi Sugiyama
  3. Online Ad Allocation with Predictions ↗Fabian Spaeh, Alina Ene
  4. Online Constrained Meta-Learning: Provable Guarantees for Generalization ↗Siyuan Xu, Minghui Zhu
  5. Online Control for Meta-optimization ↗Xinyi Chen, Elad Hazan
  6. Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms ↗Dheeraj Baby, Saurabh Garg, Tzu-Ching Yen et al.
  7. Online Learning under Adversarial Nonlinear Constraints ↗Pavel Kolev, Georg Martius, Michael Muehlebach
  8. Online PCA in Converging Self-consistent Field Equations ↗Xihan Li, Xiang 'Anthony' Chen, Rasul Tutunov et al.
  9. Online POMDP Planning with Anytime Deterministic Guarantees ↗Moran Barenboim, Vadim Indelman
  10. Online Performative Gradient Descent for Learning Nash Equilibria in Decision-Dependent Games ↗Zihan Zhu, Ethan Fang, Zhuoran Yang
  11. Online Pricing for Multi-User Multi-Item Markets ↗Yigit Efe Erginbas, Thomas A. Courtade, Kannan Ramchandran et al.
  12. Online RL in Linearly qπ-Realizable MDPs Is as Easy as in Linear MDPs If You Learn What to Ignore ↗Gellért Weisz, András György, Csaba Szepesvári
  13. Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning ↗Zixing Song, Yifei Zhang, Irwin King
  14. Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes ↗Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini
  15. Optimal Excess Risk Bounds for Empirical Risk Minimization on p-Norm Linear Regression ↗Ayoub El Hanchi, Murat A. Erdogdu
  16. Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure ↗Angela Yuan, Chris Junchi Li, Gauthier Gidel et al.
  17. Optimal Rates for Bandit Nonstochastic Control ↗Y. Jennifer Sun, Stephen Newman, Elad Hazan
  18. Optimal Transport Model Distributional Robustness ↗Van-Anh Nguyen, Thanh-Toan Do, Anh Bui et al.
  19. Optimal and Fair Encouragement Policy Evaluation and Learning ↗Angela Zhou
  20. Optimal cross-learning for contextual bandits with unknown context distributions ↗Jon Schneider, Julian Zimmert
  21. Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning ↗Georgios Kaissis, Alexander Ziller, Stefan Kolek et al.
  22. Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond 1+α Moments ↗Trung Dang, Jasper Lee, Maoyuan 'Raymond' Song et al.
  23. Optimistic Exploration in Reinforcement Learning Using Symbolic Model Estimates ↗Sarath Sreedharan, Michael Katz
  24. Optimistic Meta-Gradients ↗Sebastian Flennerhag, Tom Zahavy, Brendan O’Donoghue et al.
  25. Optimistic Rates for Multi-Task Representation Learning ↗Austin Watkins, Enayat Ullah, Thanh Nguyen-Tang et al.
  26. Optimization and Bayes: A Trade-off for Overparameterized Neural Networks ↗Zhengmian Hu, Heng Huang
  27. Optimization of Inter-group criteria for clustering with minimum size constraints ↗Eduardo Sany Laber, Lucas Murtinho
  28. Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method ↗Constantine Caramanis, Dimitris A. Fotakis, Alkis Kalavasis et al.
  29. Ordering-based Conditions for Global Convergence of Policy Gradient Methods ↗Jincheng Mei, Bo Dai, Alekh Agarwal et al.
  30. PUe: Biased Positive-Unlabeled Learning Enhancement by Causal Inference ↗Xutao Wang, Hanting Chen, Tianyu Guo et al.
  31. PaintSeg: Painting Pixels for Training-free Segmentation ↗Xiang Yuan Li, Chung-Ching Lin, Yinpeng Chen et al.
  32. Pairwise Causality Guided Transformers for Event Sequences ↗Xiao Shou, Debarun Bhattacharjya, Tian Gao et al.
  33. Parallel-mentoring for Offline Model-based Optimization ↗Can (Sam) Chen, Christopher Beckham, Zixuan Liu et al.
  34. Pareto Frontiers in Deep Feature Learning: Data, Compute, Width, and Luck ↗Benjamin Edelman, Surbhi Goel, Sham M. Kakade et al.
  35. Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model ↗Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel
  36. Partial Matrix Completion ↗Elad Hazan, Adam Tauman Kalai, Varun Kanade et al.
  37. Participatory Personalization in Classification ↗Hailey Joren, Chirag Nagpal, Katherine Heller et al.
  38. Path following algorithms for 2-regularized M-estimation with approximation guarantee ↗Yunzhang Zhu, Renxiong Liu
  39. Payoff-based Learning with Matrix Multiplicative Weights in Quantum Games ↗Kyriakos Lotidis, Panayotis Mertikopoulos, Nicholas Bambos et al.
  40. Percentile Criterion Optimization in Offline Reinforcement Learning ↗Cyrus Cousins, Elita Lobo, Marek Petrik et al.
  41. Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning ↗Austin Xu, Andrew D. McRae, Jingyan Wang et al.
  42. Persuading Farsighted Receivers in MDPs: the Power of Honesty ↗Martino Bernasconi, Matteo Castiglioni, Alberto Marchesi et al.
  43. Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior ↗Luke Travis, Kolyan Ray
  44. Policy Finetuning in Reinforcement Learning via Design of Experiments using Offline Data ↗Ruiqi Zhang, Andrea Zanette
  45. Policy Optimization in a Noisy Neighborhood: On Return Landscapes in Continuous Control ↗Nate Rahn, Pierluca D' Oro, Harley Wiltzer et al.
  46. Polyhedron Attention Module: Learning Adaptive-order Interactions ↗Tan Zhu, Fei Dou, Xinyu Wang et al.
  47. Posterior Sampling for Competitive RL: Function Approximation and Partial Observation ↗Shuang Qiu, Ziyu Dai, Han Zhong et al.
  48. Practical Contextual Bandits with Feedback Graphs ↗Mengxiao Zhang, Yuheng Zhang, Olga Vrousgou et al.
  49. Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks ↗Daogao Liu, Arun Ganesh, Sewoong Oh et al.
  50. Private Federated Frequency Estimation: Adapting to the Hardness of the Instance ↗Jingfeng Wu, Wennan Zhu, Peter Kairouz et al.
  51. Probabilistic Invariant Learning with Randomized Linear Classifiers ↗Leonardo Cotta, Gal Yehuda, Assaf Schuster et al.
  52. Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs ↗Dominik Straub, Matthias Schultheis, Heinz Koeppl et al.
  53. Projection-Free Online Convex Optimization via Efficient Newton Iterations ↗Khashayar Gatmiry, Zakaria Mhammedi
  54. ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics ↗Zhangyang Gao, Cheng Tan, Yijie Zhang et al.
  55. Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More ↗Jan Schuchardt, Yan Scholten, Stephan Günnemann
  56. Provable Guarantees for Generative Behavior Cloning: Bridging Low-Level Stability and High-Level Behavior ↗Adam Block, Ali Jadbabaie, Daniel Pfrommer et al.
  57. Provable benefits of score matching ↗Chirag Pabbaraju, Dhruv Rohatgi, Anish Prasad Sevekari et al.
  58. Provably (More) Sample-Efficient Offline RL with Options ↗Xiaoyan Hu, Ho-fung Leung
  59. Provably Efficient Offline Reinforcement Learning in Regular Decision Processes ↗Roberto Cipollone, Anders Jonsson, Alessandro Ronca et al.
  60. QuadAttacK: A Quadratic Programming Approach to Learning Ordered Top-K Adversarial Attacks ↗Thomas Paniagua, Ryan Grainger, Tianfu Wu
  61. Quasi-Monte Carlo Graph Random Features ↗Isaac Reid, Krzysztof Choromański, Adrian Weller
  62. R-divergence for Estimating Model-oriented Distribution Discrepancy ↗Zhilin Zhao, Longbing Cao
  63. RL-based Stateful Neural Adaptive Sampling and Denoising for Real-Time Path Tracing ↗Antoine Scardigli, Lukas Cavigelli, Lorenz K. Müller
  64. RaLEs: a Benchmark for Radiology Language Evaluations ↗Juanma Zambrano Chaves, Nandita Bhaskhar, Maayane Attias et al.
  65. ReHLine: Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence ↗Ben Dai, Yixuan Qiu
  66. Reconciling Competing Sampling Strategies of Network Embedding ↗Yuchen Yan, Baoyu Jing, Lihui Liu et al.
  67. Recursion in Recursion: Two-Level Nested Recursion for Length Generalization with Scalability ↗Jishnu Ray Chowdhury, Cornelia Caragea
  68. Refined Mechanism Design for Approximately Structured Priors via Active Regression ↗Christos Boutsikas, Petros Drineas B, Marios Mertzanidis et al.
  69. RegBN: Batch Normalization of Multimodal Data with Regularization ↗Morteza Ghahremani, Christian Wachinger
  70. Regression with Cost-based Rejection ↗Xin Cheng, Yuzhou Cao, Haobo Wang et al.
  71. Regret Minimization via Saddle Point Optimization ↗Johannes Kirschner, Alireza Bakhtiari, Kushagra Chandak et al.
  72. Regularized Behavior Cloning for Blocking the Leakage of Past Action Information ↗Seokin Seo, HyeongJoo Hwang, Hongseok Yang et al.
  73. Rehearsal Learning for Avoiding Undesired Future ↗Tian Qin, Tian-Zuo Wang, Zhi-Hua Zhou
  74. Reinforcement Learning with Fast and Forgetful Memory ↗Steven Morad, Ryan Kortvelesy, Stephan Liwicki et al.
  75. Reliable learning in challenging environments ↗Maria-Florina Balcan, Steve Hanneke, Rattana Pukdee et al.
  76. Renku: a platform for sustainable data science ↗Rok Roškar, Chandrasekhar Ramakrishnan, Michele Volpi et al.
  77. Representation Learning via Consistent Assignment of Views over Random Partitions ↗Thalles Santos Silva, Adıń Ramıŕez Rivera
  78. ResoNet: Noise-Trained Physics-Informed MRI Off-Resonance Correction ↗Alfredo De Goyeneche, Shreya Ramachandran, Ke Wang et al.
  79. Resolving the Tug-of-War: A Separation of Communication and Learning in Federated Learning ↗Junyi Li, Heng Huang
  80. Retaining Beneficial Information from Detrimental Data for Neural Network Repair ↗Junzhou Huang, Peilin Zhao, Junzhou Huang et al.
  81. Rethinking Gauss-Newton for learning over-parameterized models ↗Michael Arbel, Romain Menegaux, Pierre Wolinski
  82. Revisiting Area Convexity: Faster Box-Simplex Games and Spectrahedral Generalizations ↗Arun Jambulapati, Kevin Tian
  83. Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks ↗Ryan J. Sullivan, Akarsh Kumar, Shengyi Huang et al.
  84. Riemannian Laplace approximations for Bayesian neural networks ↗Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg et al.
  85. Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds ↗Jihun Yun, Eunho Yang
  86. Robust Concept Erasure via Kernelized Rate-Distortion Maximization ↗Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey et al.
  87. Robust Knowledge Transfer in Tiered Reinforcement Learning ↗Jiawei Huang, Niao He
  88. Robust Model Reasoning and Fitting via Dual Sparsity Pursuit ↗Xingyu Jiang, Jiayi Ma
  89. Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing ↗Shuyao Li, Yu Cheng, Ilias Diakonikolas et al.
  90. Robust and Actively Secure Serverless Collaborative Learning ↗Nicholas Franzese, Adam Dziedzic, Christopher A. Choquette-Choo et al.
  91. Robustness Guarantees for Adversarially Trained Neural Networks ↗Poorya Mianjy, Raman Arora
  92. SALSA VERDE: a machine learning attack on LWE with sparse small secrets ↗Cathy Li, Emily Wenger, Zeyuan Allen-Zhu et al.
  93. SG×P : A Sorghum Genotype × Phenotype Prediction Dataset and Benchmark ↗Zeyu Zhang, Robert Pless, Nadia Shakoor et al.
  94. SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning ↗Junhoo Lee, Jayeon Yoo, Nojun Kwak
  95. SOL: Sampling-based Optimal Linear bounding of arbitrary scalar functions ↗Yuriy Biktairov, Jyotirmoy V. Deshmukh
  96. SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning ↗Dohyeok Lee, Seungyub Han, Taehyun Cho et al.
  97. SPRING: Studying Papers and Reasoning to play Games ↗Yue Wu, So Yeon Min, Shrimai Prabhumoye et al.
  98. SQ Lower Bounds for Learning Mixtures of Linear Classifiers ↗Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun
  99. SQ Lower Bounds for Non-Gaussian Component Analysis with Weaker Assumptions ↗Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren et al.
  100. SUBP: Soft Uniform Block Pruning for 1×N Sparse CNNs Multithreading Acceleration ↗Jingyang Xiang, Siqi Li, Jun Chen et al.

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