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06/02/2023
An Adaptive Method for Weak Supervision with Drifting Data
We introduce an adaptive method with formal quality guarantees for weak ...
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05/03/2023
An Adaptive Algorithm for Learning with Unknown Distribution Drift
We develop and analyze a general technique for learning with an unknown ...
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02/05/2023
Nonparametric Density Estimation under Distribution Drift
We study nonparametric density estimation in non-stationary drift settin...
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05/25/2022
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes
We develop a rigorous mathematical analysis of zero-shot learning with a...
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11/15/2021
Neuro-Hotnet: A Graph Theoretic Approach for Brain FC Estimation
Functional connectivity (FC) for quantifying interactions between region...
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11/14/2021
Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds
We present a novel method for reducing the computational complexity of r...
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11/22/2020
Making mean-estimation more efficient using an MCMC trace variance approach: DynaMITE
The Markov-Chain Monte-Carlo (MCMC) method has been used widely in the l...
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07/16/2020
Wikipedia's Network Bias on Controversial Topics
The most important feature of Wikipedia is the presence of hyperlinks in...
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10/04/2019
A Rademacher Complexity Based Method fo rControlling Power and Confidence Level in Adaptive Statistical Analysis
While standard statistical inference techniques and machine learning gen...
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05/31/2019
Learning Equilibria of Simulation-Based Games
We tackle a fundamental problem in empirical game-theoretic analysis (EG...
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02/17/2019
On the Complexity of Anonymous Communication Through Public Networks
Anonymous channels allow users to connect to websites or communicate wit...
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12/18/2018
Uniform Convergence Bounds for Codec Selection
We frame the problem of selecting an optimal audio encoding scheme as a ...
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11/01/2018
VizRec: A framework for secure data exploration via visual representation
Visual representations of data (visualizations) are tools of great impor...
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08/24/2018
Unknown Examples & Machine Learning Model Generalization
Over the past decades, researchers and ML practitioners have come up wit...
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07/08/2018
Machine Learning in High Energy Physics Community White Paper
Machine learning is an important research area in particle physics, begi...
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01/10/2013
