Papers
1,396 papers found
From Pseudorandomness to Multi-Group Fairness and Back
Cynthia Dwork, Daniel Lee, Huijia Lin et al.
Generalization Error Bounds for Noisy, Iterative Algorithms via Maximal Leakage
Ibrahim Issa, Amedeo Roberto Esposito, Michael Gastpar
Generalization Guarantees via Algorithm-dependent Rademacher Complexity
Sarah Sachs, Tim van Erven, Liam Hodgkinson et al.
Geodesically convex $M$-estimation in metric spaces
Victor-Emmanuel Brunel
Geometric Barriers for Stable and Online Algorithms for Discrepancy Minimization
David Gamarnik, Eren C. Kizildağ, Will Perkins et al.
Implicit Balancing and Regularization: Generalization and Convergence Guarantees for Overparameterized Asymmetric Matrix Sensing
Mahdi Soltanolkotabi, Dominik Stöger, Changzhi Xie
Improper Multiclass Boosting
Nataly Brukhim, Steve Hanneke, Shay Moran
Improved dimension dependence of a proximal algorithm for sampling
Jiaojiao Fan, Bo Yuan, Yongxin Chen
Improved Discretization Analysis for Underdamped Langevin Monte Carlo
Shunshi Zhang, Sinho Chewi, Mufan Li et al.
Improved Dynamic Regret for Online Frank-Wolfe
Yuanyu Wan, Lijun Zhang, Mingli Song
Inference on Strongly Identified Functionals of Weakly Identified Functions
Andrew Bennett, Nathan Kallus, Xiaojie Mao et al.
InfoNCE Loss Provably Learns Cluster-Preserving Representations
Advait Parulekar, Liam Collins, Karthikeyan Shanmugam et al.
Information-Computation Tradeoffs for Learning Margin Halfspaces with Random Classification Noise
Ilias Diakonikolas, Jelena Diakonikolas, Daniel M. Kane et al.
Information-Directed Selection for Top-Two Algorithms
Wei You, Chao Qin, Zihao Wang et al.
Instance-Optimality in Interactive Decision Making: Toward a Non-Asymptotic Theory
Andrew J. Wagenmaker, Dylan J. Foster
Intrinsic dimensionality and generalization properties of the R-norm inductive bias
Navid Ardeshir, Daniel J. Hsu, Clayton H. Sanford
Is Planted Coloring Easier than Planted Clique?
Pravesh Kothari, Santosh S Vempala, Alexander S Wein et al.
Kernelized Diffusion Maps
Loucas Pillaud-Vivien, Francis Bach
Law of Large Numbers for Bayesian two-layer Neural Network trained with Variational Inference
Arnaud Descours, Tom Huix, Arnaud Guillin et al.
Learning and Testing Latent-Tree Ising Models Efficiently
Vardis Kandiros, Constantinos Daskalakis, Yuval Dagan et al.
Learning Hidden Markov Models Using Conditional Samples
Gaurav Mahajan, Sham Kakade, Akshay Krishnamurthy et al.
Learning Narrow One-Hidden-Layer ReLU Networks
Sitan Chen, Zehao Dou, Surbhi Goel et al.
Limits of Model Selection under Transfer Learning
Steve Hanneke, Samory Kpotufe, Yasaman Mahdaviyeh