Research Explorer
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Achievements
About
Methodology
← Optimization & Theory
Machine Learning
›
Optimization & Theory
›
Learning Theory
5312 directly classified 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
Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
NIPS 2024
Generalization Error Bounds for Two-stage Recommender Systems with Tree Structure
NIPS 2024
Is Score Matching Suitable for Estimating Point Processes?
NIPS 2024
V-PETL Bench: A Unified Visual Parameter-Efficient Transfer Learning Benchmark
NIPS 2024
Deep linear networks for regression are implicitly regularized towards flat minima
NIPS 2024
The Sample Complexity of Gradient Descent in Stochastic Convex Optimization
NIPS 2024
Compact Proofs of Model Performance via Mechanistic Interpretability
NIPS 2024
The Impact of Geometric Complexity on Neural Collapse in Transfer Learning
NIPS 2024
Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning
NIPS 2024
The Closeness of In-Context Learning and Weight Shifting for Softmax Regression
NIPS 2024
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality
NIPS 2024
Safe Reinforcement Learning with Instantaneous Constraints: The Role of Aggressive Exploration
AAAI 2024
On the cohesion and separability of average-link for hierarchical agglomerative clustering
NIPS 2024
Learning Discrete Concepts in Latent Hierarchical Models
NIPS 2024
On the Connection between Lp- and Risk Consistency and its Implications on Regularized Kernel Methods
JMLR 2024
Local to Global: Learning Dynamics and Effect of Initialization for Transformers
NIPS 2024
Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context
NIPS 2024
Algorithmic progress in language models
NIPS 2024
Testing Semantic Importance via Betting
NIPS 2024
Understanding Visual Feature Reliance through the Lens of Complexity
NIPS 2024
Improved Sample Complexity for Multiclass PAC Learning
NIPS 2024
Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
NIPS 2024
Dissecting Query-Key Interaction in Vision Transformers
NIPS 2024
Active Classification with Few Queries under Misspecification
NIPS 2024
Warm-up Free Policy Optimization: Improved Regret in Linear Markov Decision Processes
NIPS 2024
<
1
…
25
26
27
…
213
>