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)

Accountable Off-Policy Evaluation With Kernel Bellman Statistics ICML 2020 A Certifiably Globally Optimal Solution to Generalized Essential Matrix Estimation CVPR 2020 A Chance-Constrained Generative Framework for Sequence Optimization ICML 2020 A Characteristic Function Approach to Deep Implicit Generative Modeling CVPR 2020 A Characterization of Mean Squared Error for Estimator with Bagging AISTATS 2020 Achieving Fairness in the Stochastic Multi-Armed Bandit Problem AAAI 2020 A Class of Parallel Doubly Stochastic Algorithms for Large-Scale Learning JMLR 2020 A Closer Look at Accuracy vs. Robustness NeurIPS 2020 A Closer Look at Small-loss Bounds for Bandits with Graph Feedback COLT 2020 A closer look at the approximation capabilities of neural networks ICLR 2020 A Closer Look at the Optimization Landscapes of Generative Adversarial Networks ICLR 2020 A Closer Look at the Training Strategy for Modern Meta-Learning NeurIPS 2020 A Combinatorial Perspective on Transfer Learning NeurIPS 2020 A Complete Characterization of Projectivity for Statistical Relational Models IJCAI 2020 A Comprehensive Evaluation of Incremental Speech Recognition and Diarization for Conversational AI COLING 2020 A Computational Separation between Private Learning and Online Learning NeurIPS 2020 A Constraint-Based Approach to Learning and Explanation AAAI 2020 A Constructive Prediction of the Generalization Error Across Scales ICLR 2020 A Continuous-time Perspective for Modeling Acceleration in Riemannian Optimization AISTATS 2020 A convex optimization formulation for multivariate regression NeurIPS 2020 Acoustic-to-Articulatory Inversion with Deep Autoregressive Articulatory-WaveNet Interspeech 2020 A Critique of the Smooth Inverse Frequency Sentence Embeddings (Student Abstract) AAAI 2020 Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning CoRL 2020 Active Learning in the Geometric Block Model AAAI 2020 Active Learning of Conditional Mean Embeddings via Bayesian Optimisation UAI 2020