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10/07/2019
Fast and Bayes-consistent nearest neighbors
Research on nearest-neighbor methods tends to focus somewhat dichotomous...
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06/24/2019
Universal Bayes consistency in metric spaces
We show that a recently proposed 1-nearest-neighbor-based multiclass lea...
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05/28/2019
Regression via Kirszbraun Extension with Applications to Imitation Learning
Learning by demonstration is a versatile and rapid mechanism for transfe...
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02/01/2019
Estimating the Mixing Time of Ergodic Markov Chains
We address the problem of estimating the mixing time t_mix of an arbitra...
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01/31/2019
Minimax Testing of Identity to a Reference Ergodic Markov Chain
We exhibit an efficient procedure for testing, based on a single long st...
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10/04/2018
Improved generalization bounds for robust learning
We consider a model of robust learning in an adversarial environment. Th...
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10/03/2018
Agnostic Sample Compression for Linear Regression
We obtain the first positive results for bounded sample compression in t...
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09/13/2018
Minimax Learning of Ergodic Markov Chains
We compute the finite-sample minimax (modulo logarithmic factors) sample...
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05/24/2018
Learning convex polytopes with margin
We present a near-optimal algorithm for properly learning convex polytop...
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05/21/2018
Sample Compression for Real-Valued Learners
We give an algorithmically efficient version of the learner-to-compressi...
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05/21/2018
A New Lower Bound for Agnostic Learning with Sample Compression Schemes
We establish a tight characterization of the worst-case rates for the ex...
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11/06/2017
Advanced Analytics for Connected Cars Cyber Security
The vehicular connectivity revolution is fueling the automotive industry...
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08/24/2017
Mixing time estimation in reversible Markov chains from a single sample path
The spectral gap γ of a finite, ergodic, and reversible Markov chain is ...
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07/01/2014
A Bayes consistent 1-NN classifier
We show that a simple modification of the 1-nearest neighbor classifier ...
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12/02/2013
Consistency of weighted majority votes
We revisit the classical decision-theoretic problem of weighted expert v...
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09/19/2013
Predictive PAC Learning and Process Decompositions
We informally call a stochastic process learnable if it admits a general...
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06/11/2013
Efficient Classification for Metric Data
Recent advances in large-margin classification of data residing in gener...
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02/25/2013
On learning parametric-output HMMs
We present a novel approach for learning an HMM whose outputs are distri...
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02/12/2013
