Image de couverture de livre

Approximation Algorithms for D-optimal Design

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Singh, Mohit, Xie, Weijun
Format:	Preprint
Publié:	2018
Sujets:	Machine Learning Data Structures and Algorithms
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Computing Experiment-Constrained D-Optimal Designs
par: Pillai, Aditya, et autres
Publié: (2024)

Approximation Algorithms for Combinatorial Optimization with Predictions
par: Antoniadis, Antonios, et autres
Publié: (2024)

An Approximation Algorithm for Graph Label Selection
par: John, Josia, et autres
Publié: (2026)

A Simple Approximation Algorithm for Optimal Decision Tree
par: Zhuo, Zhengjia, et autres
Publié: (2025)

MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation
par: Hayderi, Alexandre, et autres
Publié: (2024)

Incremental Approximate Single-Source Shortest Paths with Predictions
par: McCauley, Samuel, et autres
Publié: (2025)

Prediction-Specific Design of Learning-Augmented Algorithms
par: Li, Sizhe, et autres
Publié: (2025)

Online Search with Predictions: Pareto-optimal Algorithm and its Applications in Energy Markets
par: Lee, Russell, et autres
Publié: (2022)

Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity
par: Amanatidis, Georgios, et autres
Publié: (2021)

Exact and Approximate Algorithms for Polytree Learning
par: Harviainen, Juha, et autres
Publié: (2026)

Sublinear Time Quantum Algorithm for Attention Approximation
par: Song, Zhao, et autres
Publié: (2026)

Guessing Efficiently for Constrained Subspace Approximation
par: Bhaskara, Aditya, et autres
Publié: (2025)

The Space Complexity of Approximating Logistic Loss
par: Dexter, Gregory, et autres
Publié: (2024)

Dynamic Spectral Clustering with Provable Approximation Guarantee
par: Laenen, Steinar, et autres
Publié: (2024)

Reweighted Solutions for Weighted Low Rank Approximation
par: Woodruff, David P., et autres
Publié: (2024)

Optimal Approximate Matrix Multiplication over Sliding Windows
par: Yao, Ziqi, et autres
Publié: (2025)

Improved Approximations for Hard Graph Problems using Predictions
par: Aamand, Anders, et autres
Publié: (2025)

Optimal Approximation -- Smoothness Tradeoffs for Soft-Max Functions
par: Epasto, Alessandro, et autres
Publié: (2020)

Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation
par: Pham, Ninh, et autres
Publié: (2025)

Efficient Sample-optimal Learning of Gaussian Tree Models via Sample-optimal Testing of Gaussian Mutual Information
par: Gayen, Sutanu, et autres
Publié: (2024)

Sublinear Sketches for Approximate Nearest Neighbor and Kernel Density Estimation
par: Danait, Ved, et autres
Publié: (2025)

Approximating splits for decision trees quickly in sparse data streams
par: Tatti, Nikolaj
Publié: (2026)

On Socially Fair Low-Rank Approximation and Column Subset Selection
par: Song, Zhao, et autres
Publié: (2024)

Approximating Fair $k$-Min-Sum-Radii in Euclidean Space
par: Drexler, Lukas, et autres
Publié: (2023)

A Faster Generalized Two-Stage Approximate Top-K
par: Samaga, Yashas, et autres
Publié: (2025)

Ridge Leverage Score Sampling for $\ell_p$ Subspace Approximation
par: Woodruff, David P., et autres
Publié: (2024)

OPTWIN: Drift identification with optimal sub-windows
par: Tosi, Mauro Dalle Lucca, et autres
Publié: (2023)

Nearly-tight Approximation Guarantees for the Improving Multi-Armed Bandits Problem
par: Blum, Avrim, et autres
Publié: (2024)

Linear Programming based Approximation to Individually Fair k-Clustering with Outliers
par: Maity, Binita, et autres
Publié: (2024)

Approximating High-Dimensional Earth Mover's Distance as Fast as Closest Pair
par: Beretta, Lorenzo, et autres
Publié: (2025)

Positional LSH: Binary Block Matrix Approximation for Attention with Linear Biases
par: Wolfson, Daniel, et autres
Publié: (2026)

Near-Optimal Algorithms for Omniprediction
par: Okoroafor, Princewill, et autres
Publié: (2025)

Near-optimal Swap Regret Minimization for Convex Losses
par: Hu, Lunjia, et autres
Publié: (2026)

MNL-Bandit with Knapsacks: a near-optimal algorithm
par: Aznag, Abdellah, et autres
Publié: (2021)

Near-optimal Active Regression of Single-Index Models
par: Li, Yi, et autres
Publié: (2025)

A Faster $k$-means++ Algorithm
par: Liang, Jiehao, et autres
Publié: (2022)

Efficient and Provable Algorithms for Covariate Shift
par: Adil, Deeksha, et autres
Publié: (2025)

Testing Noise Assumptions of Learning Algorithms
par: Goel, Surbhi, et autres
Publié: (2025)

Online Algorithms with Limited Data Retention
par: Immorlica, Nicole, et autres
Publié: (2024)

Learning-Augmented Algorithms with Explicit Predictors
par: Elias, Marek, et autres
Publié: (2024)