conftrace_
← Optimization & Theory
Machine Learning › Optimization & Theory ›

Optimization

14,983 papers

Papers per year

18
112
342
1289
1646
'05
'10
'15
'20
'25

Papers

Bethe Learning of Graphical Models via MAP Decoding AISTATS 2016
Unbounded Bayesian Optimization via Regularization AISTATS 2016
Streaming Kernel Principal Component Analysis AISTATS 2016
Global Convergence of a Grassmannian Gradient Descent Algorithm for Subspace Estimation AISTATS 2016
Online (and Offline) Robust PCA: Novel Algorithms and Performance Guarantees AISTATS 2016
Asynchronous Parallel Learning for Neural Networks and Structured Models with Dense Features COLING 2016
A General Optimization Framework for Multi-Document Summarization Using Genetic Algorithms and Swarm Intelligence COLING 2016
A Hybrid Deep Learning Architecture for Sentiment Analysis COLING 2016
Product Review Summarization by Exploiting Phrase Properties COLING 2016
D-GloVe: A Feasible Least Squares Model for Estimating Word Embedding Densities COLING 2016
Incremental Global Event Extraction COLING 2016
Hybrid Question Answering over Knowledge Base and Free Text COLING 2016
Integrating Distributional and Lexical Information for Semantic Classification of Words using MRMF COLING 2016
Corpus Fusion for Emotion Classification COLING 2016
A Novel Fast Framework for Topic Labeling Based on Similarity-preserved Hashing COLING 2016
An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives COLT 2016
Policy Error Bounds for Model-Based Reinforcement Learning with Factored Linear Models COLT 2016
Highly-Smooth Zero-th Order Online Optimization COLT 2016
Dropping Convexity for Faster Semi-definite Optimization COLT 2016
A Light Touch for Heavily Constrained SGD COLT 2016
Asymptotic behavior of \ell_p-based Laplacian regularization in semi-supervised learning COLT 2016
Optimal rates for total variation denoising COLT 2016
Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja’s Algorithm COLT 2016
Time series prediction and online learning COLT 2016
Gradient Descent Only Converges to Minimizers COLT 2016