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Methodology
← Optimization & Theory
Machine Learning
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Optimization & Theory
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Theory
4950 directly classified papers
Papers per year
2000: 1
2001: 2
2002: 3
2003: 3
2004: 9
2005: 4
2006: 32
2007: 25
2008: 31
2009: 25
2010: 37
2011: 37
2012: 45
2013: 76
2014: 66
2015: 72
2016: 102
2017: 156
2018: 246
2019: 353
2020: 447
2021: 567
2022: 646
2023: 741
2024: 670
2025: 426
2026: 128
Papers
Learning better with Dale’s Law: A Spectral Perspective
NIPS 2023
Moral Responsibility for AI Systems
NIPS 2023
On Translations between ML Models for XAI Purposes
IJCAI 2023
Proportionality Guarantees in Elections with Interdependent Issues
IJCAI 2023
The #DNN-Verification Problem: Counting Unsafe Inputs for Deep Neural Networks
IJCAI 2023
One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning
AISTATS 2023
Coarse-Grained Smoothness for Reinforcement Learning in Metric Spaces
AISTATS 2023
On double-descent in uncertainty quantification in overparametrized models
AISTATS 2023
Discovering the Real Association: Multimodal Causal Reasoning in Video Question Answering
CVPR 2023
Investigating data partitioning strategies for crosslinguistic low-resource ASR evaluation
EACL 2023
Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions
ACL 2023
Mining Effective Features Using Quantum Entropy for Humor Recognition
EACL 2023
Can Language Models Be Tricked by Language Illusions? Easier with Syntax, Harder with Semantics
CONLL 2023
Learning on Manifolds: Universal Approximations Properties using Geometric Controllability Conditions for Neural ODEs
L4DC 2023
Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning
NIPS 2023
On the inconsistency of separable losses for structured prediction
EACL 2023
“World Knowledge” in Multiple Choice Reading Comprehension
EACL 2023
Riemannian SAM: Sharpness-Aware Minimization on Riemannian Manifolds
NIPS 2023
Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization
NIPS 2023
Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions
NIPS 2023
It’s about Time: Rethinking Evaluation on Rumor Detection Benchmarks using Chronological Splits
EACL 2023
Analysis of Mean Opinion Scores in Subjective Evaluation of Synthetic Speech Based on Tail Probabilities
INTERSPEECH 2023
Why We Should Report the Details in Subjective Evaluation of TTS More Rigorously
INTERSPEECH 2023
Vote’n’Rank: Revision of Benchmarking with Social Choice Theory
EACL 2023
Three Iterations of (d − 1)-WL Test Distinguish Non Isometric Clouds of d-dimensional Points
NIPS 2023
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