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← Optimization & Theory
Machine Learning
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Optimization & Theory
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Learning Theory
5,312 papers
Papers per year
2001: 1
2002: 16
2003: 16
2004: 15
2005: 17
2006: 30
2007: 32
2008: 32
2009: 34
2010: 66
2011: 76
2012: 74
2013: 94
2014: 115
2015: 123
2016: 128
2017: 185
2018: 219
2019: 390
2020: 466
2021: 640
2022: 664
2023: 799
2024: 688
2025: 307
2026: 85
Papers
On Optimal Learning Under Targeted Data Poisoning
NIPS 2022
Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective
NIPS 2022
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent
NIPS 2022
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning
NIPS 2022
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization
NIPS 2022
Black-Box Generalization: Stability of Zeroth-Order Learning
NIPS 2022
On the Stability and Scalability of Node Perturbation Learning
NIPS 2022
Differentially Private Learning with Margin Guarantees
NIPS 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks
NIPS 2022
On Robust Multiclass Learnability
NIPS 2022
Improved Fine-Tuning by Better Leveraging Pre-Training Data
NIPS 2022
On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias
NIPS 2022
Benefits of Additive Noise in Composing Classes with Bounded Capacity
NIPS 2022
In What Ways Are Deep Neural Networks Invariant and How Should We Measure This?
NIPS 2022
Optimal Weak to Strong Learning
NIPS 2022
The Power and Limitation of Pretraining-Finetuning for Linear Regression under Covariate Shift
NIPS 2022
Single-pass Streaming Lower Bounds for Multi-armed Bandits Exploration with Instance-sensitive Sample Complexity
NIPS 2022
Learning Two-Player Markov Games: Neural Function Approximation and Correlated Equilibrium
NIPS 2022
Near-Optimal Regret for Adversarial MDP with Delayed Bandit Feedback
NIPS 2022
A Unifying Framework for Online Optimization with Long-Term Constraints
NIPS 2022
A Simple and Optimal Policy Design for Online Learning with Safety against Heavy-tailed Risk
NIPS 2022
The Franz-Parisi Criterion and Computational Trade-offs in High Dimensional Statistics
NIPS 2022
Structural Analysis of Branch-and-Cut and the Learnability of Gomory Mixed Integer Cuts
NIPS 2022
When are Local Queries Useful for Robust Learning?
NIPS 2022
Near-Optimal Goal-Oriented Reinforcement Learning in Non-Stationary Environments
NIPS 2022
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