conftrace_

randomized algorithm

112 papers

Explore in graph

Co-occurring keywords

low-rank approximation (323) matrix sketching (61) convex optimization (1321) dimensionality reduction (720) numerical linear algebra (35) competitive analysis (53) online algorithm (445) competitive ratio (74) principal component analysis (316) approximation algorithm (630)

Papers

Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling AISTATS 2020
Dependent randomized rounding for clustering and partition systems with knapsack constraints AISTATS 2020
Exploiting the Surrogate Gap in Online Multiclass Classification NIPS 2020
Online Algorithms for Multi-shop Ski Rental with Machine Learned Advice NIPS 2020
A Randomized Algorithm to Reduce the Support of Discrete Measures NIPS 2020
Randomized Iterative Algorithms for Fisher Discriminant Analysis UAI 2019
Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration NIPS 2019
Ultra Fast Medoid Identification via Correlated Sequential Halving NIPS 2019
A Tighter Analysis of Randomised Policy Iteration UAI 2019
SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration Without Correspondences CVPR 2019
Lower Bounds for Parallel and Randomized Convex Optimization COLT 2019
The xyz algorithm for fast interaction search in high-dimensional data JMLR 2018
Fast Randomized PCA for Sparse Data ACML 2018
An Iterative, Sketching-based Framework for Ridge Regression ICML 2018
Stochastic Spectral and Conjugate Descent Methods NIPS 2018
An Empirical Evaluation of Sketched SVD and its Application to Leverage Score Ordering ACML 2018
Error Estimation for Randomized Least-Squares Algorithms via the Bootstrap ICML 2018
Adaptive Randomized Dimension Reduction on Massive Data JMLR 2017
When Cyclic Coordinate Descent Outperforms Randomized Coordinate Descent NIPS 2017
Single-Pass PCA of Large High-Dimensional Data IJCAI 2017
Fast k-Nearest Neighbour Search via Dynamic Continuous Indexing ICML 2016
Revisiting the Nyström Method for Improved Large-scale Machine Learning JMLR 2016
A Subspace Learning Approach for High Dimensional Matrix Decomposition with Efficient Column/Row Sampling ICML 2016
Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares JMLR 2016
SPALS: Fast Alternating Least Squares via Implicit Leverage Scores Sampling NIPS 2016