7 citations · 9 across the 13 of their papers we have counts for
14 papers
Sparse Offline Reinforcement Learning with Corruption Robustness
Nam Phuong Tran, Andi Nika, Goran Radanovic +2
We investigate robustness to strong data corruption in offline sparse reinforcement learning (RL). In our setting, an adversary may arbitrarily perturb a fraction of the collected…
Symmetric Linear Bandits with Hidden Symmetry
Nam Phuong Tran, The Anh Ta, Debmalya Mandal +1
High-dimensional linear bandits with low-dimensional structure have received considerable attention in recent studies due to their practical significance. The most common structure…
Learning the Expected Core of Strictly Convex Stochastic Cooperative Games
Nam Phuong Tran, The Anh Ta, Shuqing Shi +3
Reward allocation, also known as the credit assignment problem, has been an important topic in economics, engineering, and machine learning. An important concept in reward allocati…
Examining the Effects of Degree Distribution and Homophily in Graph Learning Models
Mustafa Yasir, John Palowitch, Anton Tsitsulin +2
Despite a surge in interest in GNN development, homogeneity in benchmarking datasets still presents a fundamental issue to GNN research. GraphWorld is a recent solution which uses…
Predicting COVID-19 pandemic by spatio-temporal graph neural networks: A New Zealand's study
Viet Bach Nguyen, Truong Son Hy, Long Tran-Thanh +1
Modeling and simulations of pandemic dynamics play an essential role in understanding and addressing the spreading of highly infectious diseases such as COVID-19. In this work, we…
Achieving Better Regret against Strategic Adversaries
Le Cong Dinh, Tri-Dung Nguyen, Alain Zemkoho +1
We study online learning problems in which the learner has extra knowledge about the adversary's behaviour, i.e., in game-theoretic settings where opponents typically follow some n…
Invariant Lipschitz Bandits: A Side Observation Approach
Nam Phuong Tran, Long Tran-Thanh
Symmetry arises in many optimization and decision-making problems, and has attracted considerable attention from the optimization community: By utilizing the existence of such symm…
Multi-Player Bandits Robust to Adversarial Collisions
Shivakumar Mahesh, Anshuka Rangi, Haifeng Xu +1
Motivated by cognitive radios, stochastic Multi-Player Multi-Armed Bandits has been extensively studied in recent years. In this setting, each player pulls an arm, and receives a r…
Understanding the Limits of Poisoning Attacks in Episodic Reinforcement Learning
Anshuka Rangi, Haifeng Xu, Long Tran-Thanh +1
To understand the security threats to reinforcement learning (RL) algorithms, this paper studies poisoning attacks to manipulate \emph{any} order-optimal learning algorithm towards…
HierarchyNet: Learning to Summarize Source Code with Heterogeneous Representations
Minh Huynh Nguyen, Nghi D. Q. Bui, Truong Son Hy +2
We propose a novel method for code summarization utilizing Heterogeneous Code Representations (HCRs) and our specially designed HierarchyNet. HCRs effectively capture essential cod…
Playing Coopetitive Polymatrix Games with Small Manipulation Cost
Shivakumar Mahesh, Nicholas Bishop, Le Cong Dinh +1
Iterated coopetitive games capture the situation when one must efficiently balance between cooperation and competition with the other agents over time in order to win the game (e.g…
Online Markov Decision Processes with Non-oblivious Strategic Adversary
Le Cong Dinh, David Henry Mguni, Long Tran-Thanh +2
We study a novel setting in Online Markov Decision Processes (OMDPs) where the loss function is chosen by a non-oblivious strategic adversary who follows a no-external regret algor…
Sequential Blocked Matching
Nicholas Bishop, Hau Chan, Debmalya Mandal +1
We consider a sequential blocked matching (SBM) model where strategic agents repeatedly report ordinal preferences over a set of services to a central planner. The planner's goal i…
Exploiting No-Regret Algorithms in System Design
Le Cong Dinh, Nick Bishop, Long Tran-Thanh
We investigate a repeated two-player zero-sum game setting where the column player is also a designer of the system, and has full control on the design of the payoff matrix. In add…