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Methodology
← Optimization & Theory
Machine Learning
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Optimization & Theory
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Statistical Learning
4076 directly classified papers
Papers per year
2001: 2
2002: 8
2003: 9
2004: 7
2005: 9
2006: 34
2007: 37
2008: 34
2009: 41
2010: 62
2011: 68
2012: 81
2013: 109
2014: 120
2015: 99
2016: 149
2017: 160
2018: 205
2019: 285
2020: 376
2021: 433
2022: 447
2023: 577
2024: 488
2025: 192
2026: 44
Papers
CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference
AISTATS 2024
Equivariant bootstrapping for uncertainty quantification in imaging inverse problems
AISTATS 2024
Mind the Gap: A Causal Perspective on Bias Amplification in Prediction & Decision-Making
NIPS 2024
On the Stability and Generalization of Meta-Learning
NIPS 2024
Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data
NIPS 2024
Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation
EMNLP 2024
Efficient multi-prompt evaluation of LLMs
NIPS 2024
CONTESTS: a Framework for Consistency Testing of Span Probabilities in Language Models
EMNLP 2024
PAC-Bayes-Chernoff bounds for unbounded losses
NIPS 2024
API Is Enough: Conformal Prediction for Large Language Models Without Logit-Access
EMNLP 2024
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm
NIPS 2024
Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit
NIPS 2024
Order of Magnitude Speedups for LLM Membership Inference
EMNLP 2024
Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?
NIPS 2024
Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics
NIPS 2024
Effect of Ambient-Intrinsic Dimension Gap on Adversarial Vulnerability
AISTATS 2024
Mitigating Frequency Bias and Anisotropy in Language Model Pre-Training with Syntactic Smoothing
EMNLP 2024
Precise Model Benchmarking with Only a Few Observations
EMNLP 2024
Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models
NIPS 2024
Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems
NIPS 2024
Is Score Matching Suitable for Estimating Point Processes?
NIPS 2024
Robust group and simultaneous inferences for high-dimensional single index model
NIPS 2024
What Makes Models Compositional? A Theoretical View
IJCAI 2024
Model Collapse Demystified: The Case of Regression
NIPS 2024
Capturing the denoising effect of PCA via compression ratio
NIPS 2024
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