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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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828
3,646
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2000
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Papers (including subtopics)

In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization NeurIPS 2024 In-context Learning on Function Classes Unveiled for Transformers ICML 2024 In-Context Learning State Vector with Inner and Momentum Optimization NeurIPS 2024 In-Context Learning through the Bayesian Prism ICLR 2024 In-Context Learning with Representations: Contextual Generalization of Trained Transformers NeurIPS 2024 In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness NeurIPS 2024 Incorporating Exponential Smoothing into MLP: a Simple but Effective Sequence Model NAACL 2024 Incorporating Serverless Computing into P2P Networks for ML Training: In-Database Tasks and Their Scalability Implications (Student Abstract) AAAI 2024 Incorporating Surrogate Gradient Norm to Improve Offline Optimization Techniques NeurIPS 2024 Increasing information for model predictive control with semi-Markov decision processes L4DC 2024 Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates AAAI 2024 Incremental Randomized Smoothing Certification ICLR 2024 Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference ICLR 2024 Indirectly Parameterized Concrete Autoencoders ICML 2024 Individual Causal Structure Learning from Population Data IJCAI 2024 Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning ICML 2024 Inducing Point Operator Transformer: A Flexible and Scalable Architecture for Solving PDEs AAAI 2024 Inertial Algorithm with Dry Fraction and Convolutional Sparse Coding for 3D Localization with Light Field Microscopy AAAI 2024 Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models NeurIPS 2024 Inexact Augmented Lagrangian Methods for Conic Optimization: Quadratic Growth and Linear Convergence NeurIPS 2024 Inexact Newton-type Methods for Optimisation with Nonnegativity Constraints ICML 2024 Infeasible Deterministic, Stochastic, and Variance-Reduction Algorithms for Optimization under Orthogonality Constraints JMLR 2024 Inference and Learning in Dynamic Decision Networks Using Knowledge Compilation AAAI 2024 Inference for Optimal Linear Treatment Regimes in Personalized Decision-making UAI 2024 Inference of nonlinear causal effects with application to TWAS with GWAS summary data CLeaR 2024