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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

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Papers (including subtopics)

Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation NeurIPS 2018 Breaking the Span Assumption Yields Fast Finite-Sum Minimization NeurIPS 2018 Bridging Languages through Images with Deep Partial Canonical Correlation Analysis ACL 2018 Bringing replication and reproduction together with generalisability in NLP: Three reproduction studies for Target Dependent Sentiment Analysis COLING 2018 BRUNO: A Deep Recurrent Model for Exchangeable Data NeurIPS 2018 Bucket Renormalization for Approximate Inference ICML 2018 Budgeted Experiment Design for Causal Structure Learning ICML 2018 Building Sparse Deep Feedforward Networks using Tree Receptive Fields IJCAI 2018 But How Does It Work in Theory? Linear SVM with Random Features NeurIPS 2018 Butterfly Effects in Frame Semantic Parsing: impact of data processing on model ranking COLING 2018 Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates ICML 2018 Byzantine Stochastic Gradient Descent NeurIPS 2018 CaLcs: Continuously Approximating Longest Common Subsequence for Sequence Level Optimization EMNLP 2018 Calibrating Noise to Variance in Adaptive Data Analysis COLT 2018 Camera Pose Estimation With Unknown Principal Point CVPR 2018 Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means AISTATS 2018 Canonical Tensor Decomposition for Knowledge Base Completion ICML 2018 Can recurrent neural networks warp time? ICLR 2018 Can We Gain More from Orthogonality Regularizations in Training Deep Networks? NeurIPS 2018 Can We Trust the Bootstrap in High-dimensions? The Case of Linear Models JMLR 2018 Capturing and Enhancing In Situ System Observability for Failure Detection OSDI 2018 Card-660: Cambridge Rare Word Dataset - a Reliable Benchmark for Infrequent Word Representation Models EMNLP 2018 Cascaded Low Rank and Sparse Representation on Grassmann Manifolds IJCAI 2018 Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice JMLR 2018 Catalyst for Gradient-based Nonconvex Optimization AISTATS 2018