Skip to content
conftrace_

Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
'5
'10
'15
'20
'25

Papers (including subtopics)

CarbonNovo: Joint Design of Protein Structure and Sequence Using a Unified Energy-based Model ICML 2024 Cardinality-Aware Set Prediction and Top-k Classification NeurIPS 2024 Careful with that Scalpel: Improving Gradient Surgery with an EMA ICML 2024 Carrot and Stick: Eliciting Comparison Data and Beyond NeurIPS 2024 Cascade of phase transitions in the training of energy-based models NeurIPS 2024 Cascade Speculative Drafting for Even Faster LLM Inference NeurIPS 2024 Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning ICML 2024 Catch-Up Mix: Catch-Up Class for Struggling Filters in CNN AAAI 2024 Categorial Grammar Induction with Stochastic Category Selection COLING 2024 Categorical Flow Matching on Statistical Manifolds NeurIPS 2024 Categorical Generative Model Evaluation via Synthetic Distribution Coarsening AISTATS 2024 CATT: Character-based Arabic Tashkeel Transformer ACL 2024 Cauchy-Schwarz Divergence Information Bottleneck for Regression ICLR 2024 Causal Bandits: The Pareto Optimal Frontier of Adaptivity, a Reduction to Linear Bandits, and Limitations around Unknown Marginals ICML 2024 Causal Bandits with General Causal Models and Interventions AISTATS 2024 CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes NeurIPS 2024 Causal-CoG: A Causal-Effect Look at Context Generation for Boosting Multi-modal Language Models CVPR 2024 Causal Discovery Inspired Unsupervised Domain Adaptation for Emotion-Cause Pair Extraction EMNLP 2024 Causal Discovery Under Local Privacy CLeaR 2024 Causal Estimation of Memorisation Profiles ACL 2024 Causal Inference in the Closed-Loop: Marginal Structural Models for Sequential Excursion Effects NeurIPS 2024 Causality-enhanced Discreted Physics-informed Neural Networks for Predicting Evolutionary Equations IJCAI 2024 CausalLM is not optimal for in-context learning ICLR 2024 Causal Modeling with Stationary Diffusions AISTATS 2024 Causal Optimal Transport of Abstractions CLeaR 2024