conftrace_

Optimization

14,850 papers (55 classified directly here)

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

Continuous Optimization (4,424) Stochastic Methods (2,991) Combinatorial Optimization (2,615) Online Algorithms (2,404) Optimization (1,521) Game Theory (1,046) Convex Optimization (864) Discrete Optimization (721) Optimal Transport (474) Sparse Optimization (416) Optimal Control (271) Global Optimization (200) Non-Convex Optimization (182) Distributed Learning (164) Approximation Algorithms (162) Multi-Objective Optimization (151) Distributed Optimization (136) Bayesian Optimization (132) Theory (109) Compressed Sensing (102) Algorithms (89) Robust Optimization (86) Submodular Optimization (77) Kernel Methods (75) Evolutionary Algorithm (72) Linear Programming (54) Tensor Decomposition (48) Bilevel Optimization (42) Integer Programming (38) Matrix Completion (33) Algorithm (21) Regularization (11)

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Papers (including subtopics)

Directed Acyclic Graph Structure Learning from Dynamic Graphs AAAI 2023 Disaggregating Stateful Network Functions NSDI 2023 Discovering Many Diverse Solutions with Bayesian Optimization AISTATS 2023 Discrete Continuous Optimization Framework for Simultaneous Clustering and Training in Mixture Models ICML 2023 Discrete Langevin Samplers via Wasserstein Gradient Flow AISTATS 2023 Discrete-Smoothness in Online Algorithms with Predictions NeurIPS 2023 Discrete Variational Calculus for Accelerated Optimization JMLR 2023 DISCS: A Benchmark for Discrete Sampling NeurIPS 2023 Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning ICML 2023 Distributed Algorithms for U-statistics-based Empirical Risk Minimization JMLR 2023 Distributed Bundle Adjustment with Block-Based Sparse Matrix Compression for Super Large Scale Datasets ICCV 2023 Distributed Contextual Linear Bandits with Minimax Optimal Communication Cost ICML 2023 Distributed Linear Bandits under Communication Constraints ICML 2023 Distributed Projection-Free Online Learning for Smooth and Convex Losses AAAI 2023 Distributed Sparse Regression via Penalization JMLR 2023 Distributed Stochastic Nested Optimization for Emerging Machine Learning Models: Algorithm and Theory AAAI 2023 Distributionally Robust Bayesian Optimization with φ-divergences NeurIPS 2023 Diverse Approximations for Monotone Submodular Maximization Problems with a Matroid Constraint IJCAI 2023 Diversity Maximization in the Presence of Outliers AAAI 2023 Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions ICML 2023 DMIS: Dynamic Mesh-Based Importance Sampling for Training Physics-Informed Neural Networks AAAI 2023 Does Momentum Help in Stochastic Optimization? A Sample Complexity Analysis. UAI 2023 DoG is SGD’s Best Friend: A Parameter-Free Dynamic Step Size Schedule ICML 2023 Don't be so Monotone: Relaxing Stochastic Line Search in Over-Parameterized Models NeurIPS 2023 DOTE: Rethinking (Predictive) WAN Traffic Engineering NSDI 2023