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Debabrota Basu
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2020 – today
- 2024
- [j7]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) - [c36]Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt P. Dubhashi:
Pure Exploration in Bandits with Linear Constraints. AISTATS 2024: 334-342 - [c35]Shubhada Agrawal, Timothée Mathieu, Debabrota Basu, Odalric-Ambrym Maillard:
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption. ALT 2024: 74-124 - [c34]Hannes Eriksson, Tommy Tram, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis:
Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer. AAMAS 2024: 516-524 - [c33]Achraf Azize, Debabrota Basu:
Open Problem: What is the Complexity of Joint Differential Privacy in Linear Contextual Bandits? COLT 2024: 5306-5311 - [c32]Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo:
Augmented Bayesian Policy Search. ICLR 2024 - [c31]Achraf Azize, Debabrota Basu:
Concentrated Differential Privacy for Bandits. SaTML 2024: 78-109 - [i36]Reabetswe M. Nkhumise, Debabrota Basu, Tony J. Prescott, Aditya Gilra:
Measuring Exploration in Reinforcement Learning via Optimal Transport in Policy Space. CoRR abs/2402.09113 (2024) - [i35]Achraf Azize, Debabrota Basu:
How Much Does Each Datapoint Leak Your Privacy? Quantifying the Per-datum Membership Leakage. CoRR abs/2402.10065 (2024) - [i34]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 abs/2403.07151 (2024) - [i33]Sunrit Chakraborty, Saptarshi Roy, Debabrota Basu:
FLIPHAT: Joint Differential Privacy for High Dimensional Sparse Linear Bandits. CoRR abs/2405.14038 (2024) - [i32]Achraf Azize, Marc Jourdan, Aymen Al Marjani, Debabrota Basu:
Differentially Private Best-Arm Identification. CoRR abs/2406.06408 (2024) - [i31]Mahdi Kallel, Debabrota Basu, Riad Akrour, Carlo D'Eramo:
Augmented Bayesian Policy Search. CoRR abs/2407.04864 (2024) - [i30]Naheed Anjum Arafat, Debabrota Basu, Yulia R. Gel, Yuzhou Chen:
When Witnesses Defend: A Witness Graph Topological Layer for Adversarial Graph Learning. CoRR abs/2409.14161 (2024) - 2023
- [c30]Reda Ouhamma, Debabrota Basu, Odalric Maillard:
Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration & Planning. AAAI 2023: 9336-9344 - [c29]Bishwamittra Ghosh
, Debabrota Basu
"How Biased are Your Features?": Computing Fairness Influence Functions with Global Sensitivity Analysis. FAccT 2023: 138-148 - [c28]Edwige Cyffers, Aurélien Bellet, Debabrota Basu:
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning. ICML 2023: 6683-6711 - [c27]Achraf Azize, Marc Jourdan, Aymen Al Marjani, Debabrota Basu:
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence. NeurIPS 2023 - [c26]Pratik Karmakar, Debabrota Basu:
Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack. NeurIPS 2023 - [i29]Pratik Karmakar, Debabrota Basu:
Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack using Public Data. CoRR abs/2302.08466 (2023) - [i28]Hannes Eriksson, Debabrota Basu, Tommy Tram, Mina Alibeigi, Christos Dimitrakakis
Reinforcement Learning in the Wild with Maximum Likelihood-based Model Transfer. CoRR abs/2302.09273 (2023) - [i27]Riccardo Della Vecchia, Debabrota Basu:
Online Instrumental Variable Regression: Regret Analysis and Bandit Feedback. CoRR abs/2302.09357 (2023) - [i26]Edwige Cyffers, Aurélien Bellet, Debabrota Basu:
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning. CoRR abs/2302.12559 (2023) - [i25]Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt P. Dubhashi:
Pure Exploration in Bandits with Linear Constraints. CoRR abs/2306.12774 (2023) - [i24]Achraf Azize, Debabrota Basu:
Interactive and Concentrated Differential Privacy for Bandits. CoRR abs/2309.00557 (2023) - [i23]Achraf Azize, Marc Jourdan, Aymen Al Marjani, Debabrota Basu:
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence. CoRR abs/2309.02202 (2023) - [i22]Shubhada Agrawal, Timothée Mathieu, Debabrota Basu, Odalric-Ambrym Maillard:
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption. CoRR abs/2309.16563 (2023) - 2022
- [c25]Bishwamittra Ghosh
Algorithmic Fairness Verification with Graphical Models. AAAI 2022: 9539-9548 - [c24]Junxiong Wang, Debabrota Basu, Immanuel Trummer:
Procrastinated Tree Search: Black-Box Optimization with Delayed, Noisy, and Multi-Fidelity Feedback. AAAI 2022: 10381-10390 - [c23]Thomas Kleine Buening, Meirav Segal, Debabrota Basu, Anne-Marie George
On Meritocracy in Optimal Set Selection. EAAMO 2022: 20:1-20:14 - [c22]Achraf Azize, Debabrota Basu:
When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits. NeurIPS 2022 - [c21]Hannes Eriksson
SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning. UAI 2022: 631-640 - [i21]Debabrota Basu, Odalric-Ambrym Maillard, Timothée Mathieu:
Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic Algorithm. CoRR abs/2203.03186 (2022) - [i20]Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis:
Risk-Sensitive Bayesian Games for Multi-Agent Reinforcement Learning under Policy Uncertainty. CoRR abs/2203.10045 (2022) - [i19]Yannis Flet-Berliac, Debabrota Basu:
SAAC: Safe Reinforcement Learning as an Adversarial Game of Actor-Critics. CoRR abs/2204.09424 (2022) - [i18]Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel:
How Biased is Your Feature?: Computing Fairness Influence Functions with Global Sensitivity Analysis. CoRR abs/2206.00667 (2022) - [i17]Achraf Azize, Debabrota Basu:
When Privacy Meets Partial Information: A Refined Analysis of Differentially Private Bandits. CoRR abs/2209.02570 (2022) - [i16]Reda Ouhamma, Debabrota Basu, Odalric-Ambrym Maillard:
Bilinear Exponential Family of MDPs: Frequentist Regret Bound with Tractable Exploration and Planning. CoRR abs/2210.02087 (2022) - 2021
- [j6]Ashish Dandekar, Debabrota Basu, Stéphane Bressan:
Differential Privacy at Risk: Bridging Randomness and Privacy Budget. Proc. Priv. Enhancing Technol. 2021(1): 64-84 (2021) - [j5]Junxiong Wang, Immanuel Trummer, Debabrota Basu:
UDO: Universal Database Optimization using Reinforcement Learning. Proc. VLDB Endow. 14(13): 3402-3414 (2021) - [c20]Bishwamittra Ghosh
Justicia: A Stochastic SAT Approach to Formally Verify Fairness. AAAI 2021: 7554-7563 - [c19]Shirin Tavara
Federated Learning of Oligonucleotide Drug Molecule Thermodynamics with Differentially Private ADMM-Based SVM. PKDD/ECML Workshops (2) 2021: 459-467 - [c18]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: 2794-2797 - [i15]Hannes Eriksson, Debabrota Basu, Mina Alibeigi, Christos Dimitrakakis:
SENTINEL: Taming Uncertainty with Ensemble-based Distributional Reinforcement Learning. CoRR abs/2102.11075 (2021) - [i14]Thomas Kleine Buening, Meirav Segal, Debabrota Basu, Christos Dimitrakakis
Fair Set Selection: Meritocracy and Social Welfare. CoRR abs/2102.11932 (2021) - [i13]Junxiong Wang, Immanuel Trummer, Debabrota Basu:
UDO: Universal Database Optimization using Reinforcement Learning. CoRR abs/2104.01744 (2021) - [i12]Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel:
Algorithmic Fairness Verification with Graphical Models. CoRR abs/2109.09447 (2021) - [i11]Junxiong Wang, Debabrota Basu, Immanuel Trummer:
Procrastinated Tree Search: Black-box Optimization with Delayed, Noisy, and Multi-fidelity Feedback. CoRR abs/2110.07232 (2021) - 2020
- [c17]Divya Grover, Debabrota Basu, Christos Dimitrakakis:
Bayesian Reinforcement Learning via Deep, Sparse Sampling. AISTATS 2020: 3036-3045 - [c16]Naheed Anjum Arafat
Construction and Random Generation of Hypergraphs with Prescribed Degree and Dimension Sequences. DEXA (2) 2020: 130-145 - [c15]Emilio Jorge, Hannes Eriksson
Inferential Induction: A Novel Framework for Bayesian Reinforcement Learning. ICBINB@NeurIPS 2020: 43-52 - [i10]Christos Dimitrakakis, Hannes Eriksson, Emilio Jorge, Divya Grover, Debabrota Basu:
Inferential Induction: Joint Bayesian Estimation of MDPs and Value Functions. CoRR abs/2002.03098 (2020) - [i9]Ashish Dandekar, Debabrota Basu, Stéphane Bressan:
Differential Privacy at Risk: Bridging Randomness and Privacy Budget. CoRR abs/2003.00973 (2020) - [i8]Naheed Anjum Arafat, Debabrota Basu, Laurent Decreusefond, Stéphane Bressan:
Construction and Random Generation of Hypergraphs with Prescribed Degree and Dimension Sequences. CoRR abs/2004.05429 (2020) - [i7]Bishwamittra Ghosh, Debabrota Basu, Kuldeep S. Meel:
Justicia: A Stochastic SAT Approach to Formally Verify Fairness. CoRR abs/2009.06516 (2020) - [i6]Naheed Anjum Arafat, Debabrota Basu, Stéphane Bressan:
ε-net Induced Lazy Witness Complexes on Graphs. CoRR abs/2009.13071 (2020)
2010 – 2019
- 2019
- [j4]Debabrota Basu
Learn-as-you-go with Megh: Efficient Live Migration of Virtual Machines. IEEE Trans. Parallel Distributed Syst. 30(8): 1786-1801 (2019) - [c14]Ashish Dandekar, Debabrota Basu, Thomas Kister, Geong Sen Poh, Jia Xu
Privacy as a Service: Publishing Data and Models. DASFAA (3) 2019: 557-561 - [c13]Ashish Dandekar, Debabrota Basu, Stéphane Bressan:
Differentially Private Non-parametric Machine Learning as a Service. DEXA (1) 2019: 189-204 - [c12]Naheed Anjum Arafat
Topological Data Analysis with \epsilon ϵ -net Induced Lazy Witness Complex. DEXA (2) 2019: 376-392 - [c11]Debabrota Basu, Pierre Senellart, Stéphane Bressan:
BelMan: An Information-Geometric Approach to Stochastic Bandits. ECML/PKDD (3) 2019: 167-183 - [i5]Debabrota Basu, Christos Dimitrakakis, Aristide C. Y. Tossou:
Differential Privacy for Multi-armed Bandits: What Is It and What Is Its Cost? CoRR abs/1905.12298 (2019) - [i4]Aristide C. Y. Tossou, Debabrota Basu, Christos Dimitrakakis
Near-optimal Optimistic Reinforcement Learning using Empirical Bernstein Inequalities. CoRR abs/1905.12425 (2019) - [i3]Naheed Anjum Arafat, Debabrota Basu, Stéphane Bressan:
Topological Data Analysis with ε-net Induced Lazy Witness Complex. CoRR abs/1906.06122 (2019) - [i2]Aristide C. Y. Tossou, Debabrota Basu, Christos Dimitrakakis
Near-optimal Reinforcement Learning using Bayesian Quantiles. CoRR abs/1906.09114 (2019) - 2018
- [c10]Ashish Dandekar, Debabrota Basu, Stéphane Bressan:
Differential Privacy for Regularised Linear Regression. DEXA (2) 2018: 483-491 - [i1]Debabrota Basu, Pierre Senellart, Stéphane Bressan:
BelMan: Bayesian Bandits on the Belief-Reward Manifold. CoRR abs/1805.01627 (2018) - 2017
- [c9]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: 351-359 - [c8]Debabrota Basu, Xiayang Wang, Yang Hong, Haibo Chen, Stéphane Bressan:
Learn-as-You-Go with Megh: Efficient Live Migration of Virtual Machines. ICDCS 2017: 2608-2609 - 2016
- [j3]Debabrota Basu, Qian Lin, Weidong Chen, Hoang Tam Vo, Zihong Yuan, Pierre Senellart
Regularized Cost-Model Oblivious Database Tuning with Reinforcement Learning. Trans. Large Scale Data Knowl. Centered Syst. 28: 96-132 (2016) - [c7]Qing Liu, Debabrota Basu, Talel Abdessalem, Stéphane Bressan:
Top-k Queries Over Uncertain Scores. OTM Conferences 2016: 245-262 - 2015
- [j2]Saugat Bhattacharyya
Interval type-2 fuzzy logic based multiclass ANFIS algorithm for real-time EEG based movement control of a robot arm. Robotics Auton. Syst. 68: 104-115 (2015) - [c6]Debabrota Basu, Qian Lin, Weidong Chen, Hoang Tam Vo, Zihong Yuan, Pierre Senellart
Cost-Model Oblivious Database Tuning with Reinforcement Learning. DEXA (1) 2015: 253-268 - 2014
- [j1]Swagatam Das
A Spatially Informative Optic Flow Model of Bee Colony With Saccadic Flight Strategy for Global Optimization. IEEE Trans. Cybern. 44(10): 1884-1897 (2014) - [c5]Debabrota Basu, Saugat Bhattacharyya
A differential evolution based adaptive neural Type-2 Fuzzy inference system for classification of motor imagery EEG signals. FUZZ-IEEE 2014: 1253-1260 - 2013
- [c4]Shantanab Debchoudhury
Load Information Based Priority Dependant Heuristic for Manpower Scheduling Problem in Remanufacturing. SEMCCO (1) 2013: 59-67 - [c3]Souvik Kundu, Debabrota Basu, Sheli Sinha Chaudhuri:
Multipopulation-Based Differential Evolution with Speciation-Based Response to Dynamic Environments. SEMCCO (1) 2013: 222-235 - [c2]Debabrota Basu, Shantanab Debchoudhury
A Novel Improved Discrete ABC Algorithm for Manpower Scheduling Problem in Remanufacturing. SEMCCO (1) 2013: 738-749 - 2012
- [c1]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: 687-696
Coauthor Index
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last updated on 2024-10-18 20:28 CEST by the dblp team
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