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09/04/2023
Robust Online Classification: From Estimation to Denoising
We study online classification in the presence of noisy labels. The nois...
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08/08/2023
On the concentration of the maximum degree in the duplication-divergence models
We present a rigorous and precise analysis of the maximum degree and the...
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03/08/2023
Agnostic PAC Learning of k-juntas Using L2-Polynomial Regression
Many conventional learning algorithms rely on loss functions other than ...
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01/31/2023
Online Learning in Dynamically Changing Environments
We study the problem of online learning and online regret minimization w...
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09/09/2022
Expected Worst Case Regret via Stochastic Sequential Covering
We study the problem of sequential prediction and online minimax regret ...
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05/07/2022
Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm
We study the sequential general online regression, known also as the seq...
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03/22/2022
Toward Physically Realizable Quantum Neural Networks
There has been significant recent interest in quantum neural networks (Q...
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07/13/2021
A Theoretical Framework for Learning from Quantum Data
Over decades traditional information theory of source and channel coding...
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02/11/2021
On Agnostic PAC Learning using ℒ_2-polynomial Regression and Fourier-based Algorithms
We develop a framework using Hilbert spaces as a proxy to analyze PAC le...
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02/10/2021
A Low Degree Learning Algorithm for Quantum Data via Quantum Fourier
Advances in quantum information processing compel us to explore learning...
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01/28/2021
Low Complexity Approximate Bayesian Logistic Regression for Sparse Online Learning
Theoretical results show that Bayesian methods can achieve lower bounds ...
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01/25/2021
On maximum-likelihood estimation in the all-or-nothing regime
We study the problem of estimating a rank-1 additive deformation of a Ga...
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11/23/2020
Statistical and computational thresholds for the planted k-densest sub-hypergraph problem
Recovery a planted signal perturbed by noise is a fundamental problem in...
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05/20/2020
Sequential Universal Modeling for Non-Binary Sequences with Constrained Distributions
Sequential probability assignment and universal compression go hand in h...
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03/21/2020
Hidden Words Statistics for Large Patterns
We study here the so called subsequence pattern matching also known as h...
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05/02/2019
Temporal Ordered Clustering in Dynamic Networks
In temporal ordered clustering, given a single snapshot of a dynamic net...
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04/06/2019
Goodness of Fit Testing for Dynamic Networks
Numerous networks in the real world change over time, in the sense that ...
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05/23/2018
Joint String Complexity for Markov Sources: Small Data Matters
String complexity is defined as the cardinality of a set of all distinct...
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03/09/2018
The Trade-off between Privacy and Fidelity via Ehrhart Theory
As an increasing amount of data is gathered nowadays and stored in datab...
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01/03/2018