Search Results for author: Alexander G. Gray

Found 11 papers, 2 papers with code

Leveraging Theoretical Tradeoffs in Hyperparameter Selection for Improved Empirical Performance

no code implementations ICML Workshop AutoML 2021 Parikshit Ram, Alexander G. Gray, Horst Samulowitz

The tradeoffs in the excess risk incurred from data-driven learning of a single model has been studied by decomposing the excess risk into approximation, estimation and optimization errors.

Hyperparameter Optimization

Solving Constrained CASH Problems with ADMM

no code implementations17 Jun 2020 Parikshit Ram, Sijia Liu, Deepak Vijaykeerthi, Dakuo Wang, Djallel Bouneffouf, Greg Bramble, Horst Samulowitz, Alexander G. Gray

The CASH problem has been widely studied in the context of automated configurations of machine learning (ML) pipelines and various solvers and toolkits are available.


Building Bridges: Viewing Active Learning from the Multi-Armed Bandit Lens

no code implementations26 Sep 2013 Ravi Ganti, Alexander G. Gray

The design of this sampling distribution is also inspired by the analogy between active learning and multi-armed bandits.

Active Learning General Classification +1

Minimax Multi-Task Learning and a Generalized Loss-Compositional Paradigm for MTL

no code implementations NeurIPS 2012 Nishant Mehta, Dongryeol Lee, Alexander G. Gray

We show theoretically that minimax MTL tends to avoid worst case outcomes on newly drawn test tasks in the learning to learn (LTL) test setting.

Multi-Task Learning

Fast Nonparametric Conditional Density Estimation

1 code implementation20 Jun 2012 Michael P. Holmes, Alexander G. Gray, Charles Lee Isbell

Conditional density estimation generalizes regression by modeling a full density f(yjx) rather than only the expected value E(yjx).

Density Estimation Prediction Intervals

Maximum Inner-Product Search using Tree Data-structures

1 code implementation28 Feb 2012 Parikshit Ram, Alexander G. Gray

Finally we present a new data structure for increasing the efficiency of the dual-tree algorithm.

Submanifold density estimation

no code implementations NeurIPS 2009 Arkadas Ozakin, Alexander G. Gray

Kernel density estimation is the most widely-used practical method for accurate nonparametric density estimation.

Density Estimation

Rank-Approximate Nearest Neighbor Search: Retaining Meaning and Speed in High Dimensions

no code implementations NeurIPS 2009 Parikshit Ram, Dongryeol Lee, Hua Ouyang, Alexander G. Gray

The long-standing problem of efficient nearest-neighbor (NN) search has ubiquitous applications ranging from astrophysics to MP3 fingerprinting to bioinformatics to movie recommendations.

Linear-time Algorithms for Pairwise Statistical Problems

no code implementations NeurIPS 2009 Parikshit Ram, Dongryeol Lee, William March, Alexander G. Gray

Several key computational bottlenecks in machine learning involve pairwise distance computations, including all-nearest-neighbors (finding the nearest neighbor(s) for each point, e. g. in manifold learning) and kernel summations (e. g. in kernel density estimation or kernel machines).

Density Estimation

QUIC-SVD: Fast SVD Using Cosine Trees

no code implementations NeurIPS 2008 Michael P. Holmes, Jr. Isbell, Charles Lee, Alexander G. Gray

The Singular Value Decomposition is a key operation in many machine learning methods.

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