257 citations · 260 across the 7 of their papers we have counts for
11 papers
Robust Estimation Under Heterogeneous Corruption Rates
Syomantak Chaudhuri, Jerry Li, Thomas A. Courtade
We study the problem of robust estimation under heterogeneous corruption rates, where each sample may be independently corrupted with a known but non-identical probability. This se…
Managing Correlations in Data and Privacy Demand
Syomantak Chaudhuri, Thomas A. Courtade
Previous works in the differential privacy literature that allow users to choose their privacy levels typically operate under the heterogeneous differential privacy (HDP) framework…
Enhancing Feature-Specific Data Protection via Bayesian Coordinate Differential Privacy
Maryam Aliakbarpour, Syomantak Chaudhuri, Thomas A. Courtade +2
Local Differential Privacy (LDP) offers strong privacy guarantees without requiring users to trust external parties. However, LDP applies uniform protection to all data features, i…
Private Estimation when Data and Privacy Demands are Correlated
Syomantak Chaudhuri, Thomas A. Courtade
Differential Privacy (DP) is the current gold-standard for ensuring privacy for statistical queries. Estimation problems under DP constraints appearing in the literature have large…
Mean Estimation Under Heterogeneous Privacy Demands
Syomantak Chaudhuri, Konstantin Miagkov, Thomas A. Courtade
Differential Privacy (DP) is a well-established framework to quantify privacy loss incurred by any algorithm. Traditional formulations impose a uniform privacy requirement for all…
Mean Estimation Under Heterogeneous Privacy: Some Privacy Can Be Free
Syomantak Chaudhuri, Thomas A. Courtade
Differential Privacy (DP) is a well-established framework to quantify privacy loss incurred by any algorithm. Traditional DP formulations impose a uniform privacy requirement for a…
Online Target Q-learning with Reverse Experience Replay: Efficiently finding the Optimal Policy for Linear MDPs
Naman Agarwal, Syomantak Chaudhuri, Prateek Jain +2
Q-learning is a popular Reinforcement Learning (RL) algorithm which is widely used in practice with function approximation (Mnih et al., 2015). In contrast, existing theoretical re…
Compound Arbitrarily Varying Channels
Syomantak Chaudhuri, Neha Sangwan, Mayank Bakshi +2
We propose a communication model, that we call compound arbitrarily varying channels (CAVC), which unifies and generalizes compound channels and arbitrarily varying channels (AVC).…
An Optimized Signal Processing Pipeline for Syllable Detection and Speech Rate Estimation
Kamini Sabu, Syomantak Chaudhuri, Preeti Rao +1
Syllable detection is an important speech analysis task with applications in speech rate estimation, word segmentation, and automatic prosody detection. Based on the well understoo…
GuCNet: A Guided Clustering-based Network for Improved Classification
Ushasi Chaudhuri, Syomantak Chaudhuri, Subhasis Chaudhuri
We deal with the problem of semantic classification of challenging and highly-cluttered dataset. We present a novel, and yet a very simple classification technique by leveraging th…
SPAN: Spatial Pyramid Attention Network forImage Manipulation Localization
Xuefeng Hu, Zhihan Zhang, Zhenye Jiang +3
We present a novel framework, Spatial Pyramid Attention Network (SPAN) for detection and localization of multiple types of image manipulations. The proposed architecture efficientl…