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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
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Papers (including subtopics)

Towards Exact Computation of Inductive Bias IJCAI 2024 Towards Exact Gradient-based Training on Analog In-memory Computing NeurIPS 2024 Towards Explainable Joint Models via Information Theory for Multiple Intent Detection and Slot Filling AAAI 2024 Towards Explainable Monaural Speaker Separation with Auditory-based Training Interspeech 2024 Towards Fast Cognate Alignment on Imbalanced Data COLING 2024 Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph ICML 2024 Towards Generalization beyond Pointwise Learning: A Unified Information-theoretic Perspective ICML 2024 Towards General Loop Invariant Generation: A Benchmark of Programs with Memory Manipulation NeurIPS 2024 Towards General Robustness Verification of MaxPool-based Convolutional Neural Networks via Tightening Linear Approximation CVPR 2024 Towards Geometric Normalization Techniques in SE(3) Equivariant Graph Neural Networks for Physical Dynamics Simulations IJCAI 2024 Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles ICML 2024 Towards Green AI in Fine-tuning Large Language Models via Adaptive Backpropagation ICLR 2024 Towards Harmless Rawlsian Fairness Regardless of Demographic Prior NeurIPS 2024 Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox NeurIPS 2024 Towards Human-aligned Evaluation for Linear Programming Word Problems COLING 2024 Towards Interpretable Deep Local Learning with Successive Gradient Reconciliation ICML 2024 Towards Large Certified Radius in Randomized Smoothing Using Quasiconcave Optimization AAAI 2024 Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching ICLR 2024 Towards Minimax Optimality of Model-based Robust Reinforcement Learning UAI 2024 Towards model-free LQR control over rate-limited channels L4DC 2024 Towards More Accurate Diffusion Model Acceleration with A Timestep Tuner CVPR 2024 Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks EMNLP 2024 Towards Multi-Mode Outlier Robust Tensor Ring Decomposition AAAI 2024 Towards Next-Generation Logic Synthesis: A Scalable Neural Circuit Generation Framework NeurIPS 2024 Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models ICLR 2024