Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence | Fengxiang He · Tongliang Liu · Dacheng Tao |
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation | Colin Wei · Tengyu Ma |
Exact inference in structured prediction | Kevin Bello · Jean Honorio |
Globally optimal score-based learning of directed acyclic graphs in high-dimensions | Bryon Aragam · Arash Amini · Qing Zhou |
List-decodable Linear Regression | Sushrut Karmalkar · Adam Klivans · Pravesh Kothari |
On the Calibration of Multiclass Classification with Rejection | Chenri Ni · Nontawat Charoenphakdee · Junya Honda · Masashi Sugiyama |
On the Hardness of Robust Classification | Pascale Gourdeau · Varun Kanade · Marta Kwiatkowska · James Worrell |
Optimal Analysis of Subset-Selection Based L_p Low-Rank Approximation | Chen Dan · Hong Wang · Hongyang Zhang · Yuchen Zhou · Pradeep Ravikumar |
PAC-Bayes under potentially heavy tails | Matthew Holland |
Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection | Yihe Dong · Samuel Hopkins · Jerry Li |
Uniform convergence may be unable to explain generalization in deep learning | Vaishnavh Nagarajan · J. Zico Kolter |
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families | Brian Axelrod · Ilias Diakonikolas · Alistair Stewart · Anastasios Sidiropoulos · Gregory Valiant |
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks | Gaël Letarte · Pascal Germain · Benjamin Guedj · Francois Laviolette |
Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator | Karl Krauth · Stephen Tu · Benjamin Recht |
Hypothesis Set Stability and Generalization | Dylan Foster · Spencer Greenberg · Satyen Kale · Haipeng Luo · Mehryar Mohri · Karthik Sridharan |
Minimizers of the Empirical Risk and Risk Monotonicity | Marco Loog · Tom Viering · Alexander Mey |
Multiclass Learning from Contradictions | Sauptik Dhar · Vladimir Cherkassky · Mohak Shah |
On the Correctness and Sample Complexity of Inverse Reinforcement Learning | Abi Komanduru · Jean Honorio |
On the Power and Limitations of Random Features for Understanding Neural Networks | Gilad Yehudai · Ohad Shamir |
Robustness to Adversarial Perturbations in Learning from Incomplete Data | Amir Najafi · Shin-ichi Maeda · Masanori Koyama · Takeru Miyato |
Stability of Graph Scattering Transforms | Fernando Gama · Alejandro Ribeiro · Joan Bruna |
State Aggregation Learning from Markov Transition Data | Yaqi Duan · Tracy Ke · Mengdi Wang |
Toward a Characterization of Loss Functions for Distribution Learning | Nika Haghtalab · Cameron Musco · Bo Waggoner |
An Embedding Framework for Consistent Polyhedral Surrogates | Jessica Finocchiaro · Rafael Frongillo · Bo Waggoner |
Covariate-Powered Empirical Bayes Estimation | Nikolaos Ignatiadis · Stefan Wager |
Learning Bayesian Networks with Low Rank Conditional Probability Tables | Adarsh Barik · Jean Honorio |
Learning to Screen | Alon Cohen · Avinatan Hassidim · Haim Kaplan · Yishay Mansour · Shay Moran |
Limits of Private Learning with Access to Public Data | Raef Bassily · Shay Moran · Noga Alon |
Multiclass Performance Metric Elicitation | Gaurush Hiranandani · Shant Boodaghians · Ruta Mehta · Oluwasanmi Koyejo |
On the Value of Target Data in Transfer Learning | Steve Hanneke · Samory Kpotufe |
Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering | Ilias Diakonikolas · Daniel Kane · Sushrut Karmalkar · Eric Price · Alistair Stewart |
Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models | Farnam Mansouri · Yuxin Chen · Ara Vartanian · Jerry Zhu · Adish Singla |
Rates of Convergence for Large-scale Nearest Neighbor Classification | Xingye Qiao · Jiexin Duan · Guang Cheng |
What Can ResNet Learn Efficiently, Going Beyond Kernels? | Zeyuan Allen-Zhu · Yuanzhi Li |
An adaptive nearest neighbor rule for classification | Akshay Balsubramani · Sanjoy Dasgupta · yoav Freund · Shay Moran |
Distribution-Independent PAC Learning of Halfspaces with Massart Noise | Ilias Diakonikolas · Themis Gouleakis · Christos Tzamos |
Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes | Jun Yang · Shengyang Sun · Daniel Roy |
Generalization Bounds for Neural Networks via Approximate Description Length | Amit Daniely · Elad Granot |
Graph-based Discriminators: Sample Complexity and Expressiveness | Roi Livni · Yishay Mansour |
Limitations of Lazy Training of Two-layers Neural Network | Song Mei · Theodor Misiakiewicz · Behrooz Ghorbani · Andrea Montanari |
On Making Stochastic Classifiers Deterministic | Andrew Cotter · Maya Gupta · Harikrishna Narasimhan |
Semi-Parametric Efficient Policy Learning with Continuous Actions | Victor Chernozhukov · Mert Demirer · Greg Lewis · Vasilis Syrgkanis |
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity | Chulhee Yun · Suvrit Sra · Ali Jadbabaie |
The Broad Optimality of Profile Maximum Likelihood | Yi Hao · Alon Orlitsky |
Time/Accuracy Tradeoffs for Learning a ReLU with respect to Gaussian Marginals | Surbhi Goel · Sushrut Karmalkar · Adam Klivans |
A General Framework for Symmetric Property Estimation | Moses Charikar · Kirankumar Shiragur · Aaron Sidford |
Generalization Bounds in the Predict-then-Optimize Framework | Othman El Balghiti · Adam Elmachtoub · Paul Grigas · Ambuj Tewari |
Generalization Error Analysis of Quantized Compressive Learning | Xiaoyun Li · Ping Li |
Implicit Regularization of Accelerated Methods in Hilbert Spaces | Nicolò Pagliana · Lorenzo Rosasco |
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates | Jeffrey Negrea · Mahdi Haghifam · Gintare Karolina Dziugaite · Ashish Khisti · Daniel Roy |
Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin | Ilias Diakonikolas · Daniel Kane · Pasin Manurangsi |
PAC-Bayes Un-Expected Bernstein Inequality | Zakaria Mhammedi · Peter Grünwald · Benjamin Guedj |
Private Testing of Distributions via Sample Permutations | Maryam Aliakbarpour · Ilias Diakonikolas · Daniel Kane · Ronitt Rubinfeld |
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel | Colin Wei · Jason Lee · Qiang Liu · Tengyu Ma |
Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection | Xiaoyi Gu · Leman Akoglu · Alessandro Rinaldo |
Theoretical Analysis of Adversarial Learning: A Minimax Approach | Zhuozhuo Tu · Jingwei Zhang · Dacheng Tao |
Unified Sample-Optimal Property Estimation in Near-Linear Time | Yi Hao · Alon Orlitsky |