Debabrota Basu

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 70

Top Topics

Sparse Sampling

Reinforcement Learning

Differential Privacy

Top Venues

Publications

Achraf Azize, Debabrota Basu
Open Problem: What is the Complexity of Joint Differential Privacy in Linear Contextual Bandits? COLT (2024)
Achraf Azize, Debabrota Basu
Concentrated Differential Privacy for Bandits. SaTML (2024)
Shubhada Agrawal, Timothée Mathieu, Debabrota Basu, Odalric-Ambrym Maillard
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption. ALT (2024)
Timothée Mathieu, Debabrota Basu, Odalric-Ambrym Maillard
Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic Algorithms. Trans. Mach. Learn. Res. 2024 (2024)
Reabetswe M. Nkhumise, Debabrota Basu, Tony J. Prescott, Aditya Gilra
Measuring Exploration in Reinforcement Learning via Optimal Transport in Policy Space. CoRR (2024)
Sunrit Chakraborty, Saptarshi Roy, Debabrota Basu
FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear Bandits. CoRR (2024)
Achraf Azize, Marc Jourdan, Aymen Al Marjani, Debabrota Basu
Differentially Private Best-Arm Identification. CoRR (2024)
Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo
Augmented Bayesian Policy Search. ICLR (2024)
Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo
Augmented Bayesian Policy Search. CoRR (2024)
Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt P. Dubhashi
Pure Exploration in Bandits with Linear Constraints. AISTATS (2024)
Bishwamittra Ghosh, Debabrota Basu, Huazhu Fu, Yuan Wang, Renuga Kanagavelu, Jiang Jin Peng, Yong Liu, Rick Siow Mong Goh, Qingsong Wei
Don't Forget What I did?: Assessing Client Contributions in Federated Learning. CoRR (2024)
Achraf Azize, Debabrota Basu
How Much Does Each Datapoint Leak Your Privacy? Quantifying the Per-datum Membership Leakage. CoRR (2024)
Hannes Eriksson, Tommy Tram, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis
Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer. AAMAS (2024)
Edwige Cyffers, Aurélien Bellet, Debabrota Basu
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning. CoRR (2023)
Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt P. Dubhashi
Pure Exploration in Bandits with Linear Constraints. CoRR (2023)
Riccardo Della Vecchia, Debabrota Basu
Online Instrumental Variable Regression: Regret Analysis and Bandit Feedback. CoRR (2023)
Edwige Cyffers, Aurélien Bellet, Debabrota Basu
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning. ICML (2023)
Reda Ouhamma, Debabrota Basu, Odalric Maillard
Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration & Planning. AAAI (2023)
Shubhada Agrawal, Timothée Mathieu, Debabrota Basu, Odalric-Ambrym Maillard
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption. CoRR (2023)
Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel
"How Biased are Your Features?": Computing Fairness Influence Functions with Global Sensitivity Analysis. FAccT (2023)
Achraf Azize, Marc Jourdan, Aymen Al Marjani, Debabrota Basu
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence. NeurIPS (2023)
Achraf Azize, Marc Jourdan, Aymen Al Marjani, Debabrota Basu
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence. CoRR (2023)
Achraf Azize, Debabrota Basu
Interactive and Concentrated Differential Privacy for Bandits. CoRR (2023)
Pratik Karmakar, Debabrota Basu
Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack. NeurIPS (2023)
Hannes Eriksson, Debabrota Basu, Tommy Tram, Mina Alibeigi, Christos Dimitrakakis
Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer. CoRR (2023)
Pratik Karmakar, Debabrota Basu
Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack using Public Data. CoRR (2023)
Thomas Kleine Buening, Meirav Segal, Debabrota Basu, Anne-Marie George, Christos Dimitrakakis
On Meritocracy in Optimal Set Selection. EAAMO (2022)
Debabrota Basu, Odalric-Ambrym Maillard, Timothée Mathieu
Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic Algorithm. CoRR (2022)
Reda Ouhamma, Debabrota Basu, Odalric-Ambrym Maillard
Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration and Planning. CoRR (2022)
Junxiong Wang, Debabrota Basu, Immanuel Trummer
Procrastinated Tree Search: Black-Box Optimization with Delayed, Noisy, and Multi-Fidelity Feedback. AAAI (2022)
Achraf Azize, Debabrota Basu
When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits. CoRR (2022)
Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis
Risk-Sensitive Bayesian Games for Multi-Agent Reinforcement Learning under Policy Uncertainty. CoRR (2022)
Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel
How Biased is Your Feature?: Computing Fairness Influence Functions with Global Sensitivity Analysis. CoRR (2022)
Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis
SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning. UAI (2022)
Yannis Flet-Berliac, Debabrota Basu
SAAC: Safe Reinforcement Learning as an Adversarial Game of Actor-Critics. CoRR (2022)
Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel
Algorithmic Fairness Verification with Graphical Models. AAAI (2022)
Achraf Azize, Debabrota Basu
When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits. NeurIPS (2022)
Ashish Dandekar, Debabrota Basu, Stéphane Bressan
Differential Privacy at Risk: Bridging Randomness and Privacy Budget. Proc. Priv. Enhancing Technol. 2021 (1) (2021)
Junxiong Wang, Debabrota Basu, Immanuel Trummer
Procrastinated Tree Search: Black-box Optimization with Delayed, Noisy, and Multi-fidelity Feedback. CoRR (2021)
Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel
Algorithmic Fairness Verification with Graphical Models. CoRR (2021)
Thomas Kleine Buening, Meirav Segal, Debabrota Basu, Christos Dimitrakakis
Fair Set Selection: Meritocracy and Social Welfare. CoRR (2021)
Junxiong Wang, Immanuel Trummer, Debabrota Basu
Demonstrating UDO: A Unified Approach for Optimizing Transaction Code, Physical Design, and System Parameters via Reinforcement Learning. SIGMOD Conference (2021)
Junxiong Wang, Immanuel Trummer, Debabrota Basu
UDO: Universal Database Optimization using Reinforcement Learning. CoRR (2021)
Junxiong Wang, Immanuel Trummer, Debabrota Basu
UDO: Universal Database Optimization using Reinforcement Learning. Proc. VLDB Endow. 14 (13) (2021)
Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis
SENTINEL: Taming Uncertainty with Ensemble-based Distributional Reinforcement Learning. CoRR (2021)
Shirin Tavara, Alexander Schliep, Debabrota Basu
Federated Learning of Oligonucleotide Drug Molecule Thermodynamics with Differentially Private ADMM-Based SVM. PKDD/ECML Workshops (2) (2021)
Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel
Justicia: A Stochastic SAT Approach to Formally Verify Fairness. AAAI (2021)
Naheed Anjum Arafat, Debabrota Basu, Laurent Decreusefond, Stéphane Bressan
Construction and Random Generation of Hypergraphs with Prescribed Degree and Dimension Sequences. DEXA (2) (2020)
Christos Dimitrakakis, Hannes Eriksson, Emilio Jorge, Divya Grover, Debabrota Basu
Inferential Induction: Joint Bayesian Estimation of MDPs and Value Functions. CoRR (2020)
Ashish Dandekar, Debabrota Basu, Stéphane Bressan
Differential Privacy at Risk: Bridging Randomness and Privacy Budget. CoRR (2020)
Naheed Anjum Arafat, Debabrota Basu, Stéphane Bressan
ε-net Induced Lazy Witness Complexes on Graphs. CoRR (2020)
Divya Grover, Debabrota Basu, Christos Dimitrakakis
Bayesian Reinforcement Learning via Deep, Sparse Sampling. AISTATS (2020)
Naheed Anjum Arafat, Debabrota Basu, Laurent Decreusefond, Stéphane Bressan
Construction and Random Generation of Hypergraphs with Prescribed Degree and Dimension Sequences. CoRR (2020)
Emilio Jorge, Hannes Eriksson, Christos Dimitrakakis, Debabrota Basu, Divya Grover
Inferential Induction: A Novel Framework for Bayesian Reinforcement Learning. ICBINB@NeurIPS (2020)
Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel
Justicia: A Stochastic SAT Approach to Formally Verify Fairness. CoRR (2020)
Ashish Dandekar, Debabrota Basu, Thomas Kister, Geong Sen Poh, Jia Xu, Stéphane Bressan
Privacy as a Service: Publishing Data and Models. DASFAA (3) (2019)
Debabrota Basu, Pierre Senellart, Stéphane Bressan
BelMan: An Information-Geometric Approach to Stochastic Bandits. ECML/PKDD (3) (2019)
Debabrota Basu, Christos Dimitrakakis, Aristide C. Y. Tossou
Differential Privacy for Multi-armed Bandits: What Is It and What Is Its Cost? CoRR (2019)
Aristide C. Y. Tossou, Debabrota Basu, Christos Dimitrakakis
Near-optimal Reinforcement Learning using Bayesian Quantiles. CoRR (2019)
Debabrota Basu, Xiayang Wang, Yang Hong, Haibo Chen, Stéphane Bressan
Learn-as-you-go with Megh: Efficient Live Migration of Virtual Machines. IEEE Trans. Parallel Distributed Syst. 30 (8) (2019)
Ashish Dandekar, Debabrota Basu, Stéphane Bressan
Differentially Private Non-parametric Machine Learning as a Service. DEXA (1) (2019)
Aristide C. Y. Tossou, Debabrota Basu, Christos Dimitrakakis
Near-optimal Optimistic Reinforcement Learning using Empirical Bernstein Inequalities. CoRR (2019)
Naheed Anjum Arafat, Debabrota Basu, Stéphane Bressan
Topological Data Analysis with \epsilon ϵ -net Induced Lazy Witness Complex. DEXA (2) (2019)
Naheed Anjum Arafat, Debabrota Basu, Stéphane Bressan
Topological Data Analysis with ε-net Induced Lazy Witness Complex. CoRR (2019)
Debabrota Basu, Pierre Senellart, Stéphane Bressan
BelMan: Bayesian Bandits on the Belief-Reward Manifold. CoRR (2018)
Ashish Dandekar, Debabrota Basu, Stéphane Bressan
Differential Privacy for Regularised Linear Regression. DEXA (2) (2018)
Debabrota Basu, Xiayang Wang, Yang Hong, Haibo Chen, Stéphane Bressan
Learn-as-You-Go with Megh: Efficient Live Migration of Virtual Machines. ICDCS (2017)
Qing Liu, Debabrota Basu, Shruti Goel, Talel Abdessalem, Stéphane Bressan
How to Find the Best Rated Items on a Likert Scale and How Many Ratings Are Enough. DEXA (2) (2017)
Debabrota Basu, Qian Lin, Weidong Chen, Hoang Tam Vo, Zihong Yuan, Pierre Senellart, Stéphane Bressan
Regularized Cost-Model Oblivious Database Tuning with Reinforcement Learning. Trans. Large Scale Data Knowl. Centered Syst. 28 (2016)
Qing Liu, Debabrota Basu, Talel Abdessalem, Stéphane Bressan
Top-k Queries Over Uncertain Scores. OTM Conferences (2016)
Debabrota Basu, Qian Lin, Weidong Chen, Hoang Tam Vo, Zihong Yuan, Pierre Senellart, Stéphane Bressan
Cost-Model Oblivious Database Tuning with Reinforcement Learning. DEXA (1) (2015)
Saugat Bhattacharyya, Debabrota Basu, Amit Konar, D. N. Tibarewala
Interval type-2 fuzzy logic based multiclass ANFIS algorithm for real-time EEG based movement control of a robot arm. Robotics Auton. Syst. 68 (2015)
Debabrota Basu, Saugat Bhattacharyya, Dwaipayan Sardar, Amit Konar, D. N. Tibarewala, Atulya K. Nagar
A differential evolution based adaptive neural Type-2 Fuzzy inference system for classification of motor imagery EEG signals. FUZZ-IEEE (2014)
Swagatam Das, Subhodip Biswas, Bijaya K. Panigrahi, Souvik Kundu, Debabrota Basu
A Spatially Informative Optic Flow Model of Bee Colony With Saccadic Flight Strategy for Global Optimization. IEEE Trans. Cybern. 44 (10) (2014)
Shantanab Debchoudhury, Debabrota Basu, Kaizhou Gao, Ponnuthurai Nagaratnam Suganthan
Load Information Based Priority Dependant Heuristic for Manpower Scheduling Problem in Remanufacturing. SEMCCO (1) (2013)
Debabrota Basu, Shantanab Debchoudhury, Kaizhou Gao, Ponnuthurai Nagaratnam Suganthan
A Novel Improved Discrete ABC Algorithm for Manpower Scheduling Problem in Remanufacturing. SEMCCO (1) (2013)
Souvik Kundu, Debabrota Basu, Sheli Sinha Chaudhuri
Multipopulation-Based Differential Evolution with Speciation-Based Response to Dynamic Environments. SEMCCO (1) (2013)
Srinjoy Ganguly, Swahum Mukherjee, Debabrota Basu, Swagatam Das
A Novel Strategy Adaptive Genetic Algorithm with Greedy Local Search for the Permutation Flowshop Scheduling Problem. SEMCCO (2012)