Vaneet Aggarwal

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 384

Top Venues

CoRR

IEEE/ACM Trans. Netw.

IEEE Trans. Inf. Theory

ISIT

Publications

Washim Uddin Mondal, Veni Goyal, Satish V. Ukkusuri, Goutam Das, Di Wang, Mohamed-Slim Alouini, Vaneet Aggarwal
Near-perfect Coverage Manifold Estimation in Cellular Networks via conditional GAN. CoRR (2024)
Jiayu Chen, Bhargav Ganguly, Yang Xu, Yongsheng Mei, Tian Lan, Vaneet Aggarwal
Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions. CoRR (2024)
Vaneet Aggarwal, Rakhi Pratihar
Insdel codes from subspace and rank-metric codes. Discret. Math. 347 (1) (2024)
Ruibo Wang, Washim Uddin Mondal, Mustafa A. Kishk, Vaneet Aggarwal, Mohamed-Slim Alouini
Terrain-Based Coverage Manifold Estimation: Machine Learning, Stochastic Geometry, or Simulation? IEEE Open J. Commun. Soc. 5 (2024)
Washim Uddin Mondal, Vaneet Aggarwal
Sample-Efficient Constrained Reinforcement Learning with General Parameterization. CoRR (2024)
Mohammad Pedramfar, Yididiya Y. Nadew, Christopher John Quinn, Vaneet Aggarwal
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization. ICLR (2024)
Chenyi Liu, Vaneet Aggarwal, Tian Lan, Nan Geng, Yuan Yang, Mingwei Xu, Qing Li
FERN: Leveraging Graph Attention Networks for Failure Evaluation and Robust Network Design. IEEE/ACM Trans. Netw. 32 (2) (2024)
Swetha Ganesh, Vaneet Aggarwal
An Accelerated Multi-level Monte Carlo Approach for Average Reward Reinforcement Learning with General Policy Parametrization. CoRR (2024)
Vaneet Aggarwal, Washim Uddin Mondal, Qinbo Bai
Constrained Reinforcement Learning with Average Reward Objective: Model-Based and Model-Free Algorithms. Found. Trends Optim. 6 (4) (2024)
Jiayu Chen, Bhargav Ganguly, Tian Lan, Vaneet Aggarwal
Variational Offline Multi-agent Skill Discovery. CoRR (2024)
Swetha Ganesh, Jiayu Chen, Gugan Thoppe, Vaneet Aggarwal
Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries. CoRR (2024)
Dipesh Tamboli, Jiayu Chen, Kiran Pranesh Jotheeswaran, Denny Yu, Vaneet Aggarwal
Reinforced Sequential Decision-Making for Sepsis Treatment: The POSNEGDM Framework with Mortality Classifier and Transformer. CoRR (2024)
Mohammad Pedramfar, Vaneet Aggarwal
From Linear to Linearizable Optimization: A Novel Framework with Applications to Stationary and Non-stationary DR-submodular Optimization. CoRR (2024)
Washim Uddin Mondal, Veni Goyal, Satish V. Ukkusuri, Goutam Das, Di Wang, Mohamed-Slim Alouini, Vaneet Aggarwal
Near-Perfect Coverage Manifold Estimation in Cellular Networks via Conditional GAN. IEEE Netw. Lett. 6 (2) (2024)
Bhargav Ganguly, Vaneet Aggarwal
Online Federated Learning via Non-Stationary Detection and Adaptation Amidst Concept Drift. IEEE/ACM Trans. Netw. 32 (1) (2024)
Debanjan Konar, Zain Hafeez, Vaneet Aggarwal
A Bi-directional Quantum Search Algorithm. CoRR (2024)
Qinbo Bai, Washim Uddin Mondal, Vaneet Aggarwal
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes. AAAI (2024)
Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal
Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization. CoRR (2024)
Washim Uddin Mondal, Vaneet Aggarwal
Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes. AISTATS (2024)
Ciyuan Zhang, Su Wang, Vaneet Aggarwal, Borja Peleato
Coded Caching With Heterogeneous User Profiles. IEEE Trans. Inf. Theory 70 (3) (2024)
Fares Fourati, Vaneet Aggarwal, Mohamed-Slim Alouini
Stochastic Q-learning for Large Discrete Action Spaces. CoRR (2024)
Swetha Ganesh, Washim Uddin Mondal, Vaneet Aggarwal
Variance-Reduced Policy Gradient Approaches for Infinite Horizon Average Reward Markov Decision Processes. CoRR (2024)
Mohammad Pedramfar, Vaneet Aggarwal
A Generalized Approach to Online Convex Optimization. CoRR (2024)
Dipesh Tamboli, Jiayu Chen, Kiran Pranesh Jotheeswaran, Denny Yu, Vaneet Aggarwal
Reinforced Sequential Decision-Making for Sepsis Treatment: The PosNegDM Framework With Mortality Classifier and Transformer. IEEE J. Biomed. Health Informatics 28 (5) (2024)
Mohammad Pedramfar, Yididiya Y. Nadew, Christopher J. Quinn, Vaneet Aggarwal
Unified Projection-Free Algorithms for Adversarial DR-Submodular Optimization. CoRR (2024)
Qinbo Bai, Washim Uddin Mondal, Vaneet Aggarwal
Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm. CoRR (2024)
Sparsh Gupta, Debanjan Konar, Vaneet Aggarwal
A Scalable Quantum Non-local Neural Network for Image Classification. CoRR (2024)
Vaneet Aggarwal, Washim Uddin Mondal, Qinbo Bai
Constrained Reinforcement Learning with Average Reward Objective: Model-Based and Model-Free Algorithms. CoRR (2024)
Chang-Lin Chen, Bharat K. Bhargava, Vaneet Aggarwal, Basavaraj Tonshal, Amrit Gopal
A Hybrid Deep Reinforcement Learning Approach for Jointly Optimizing Offloading and Resource Management in Vehicular Networks. IEEE Trans. Veh. Technol. 73 (2) (2024)
Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model. ICLR (2024)
Seyyedali Hosseinalipour, Su Wang, Nicolò Michelusi, Vaneet Aggarwal, Christopher G. Brinton, David J. Love, Mung Chiang
Parallel Successive Learning for Dynamic Distributed Model Training Over Heterogeneous Wireless Networks. IEEE/ACM Trans. Netw. 32 (1) (2024)
Fares Fourati, Mohamed-Slim Alouini, Vaneet Aggarwal
Federated Combinatorial Multi-Agent Multi-Armed Bandits. CoRR (2024)
Fares Fourati, Christopher John Quinn, Mohamed-Slim Alouini, Vaneet Aggarwal
Combinatorial Stochastic-Greedy Bandit. AAAI (2024)
Guangchen Lan, Dong-Jun Han, Abolfazl Hashemi, Vaneet Aggarwal, Christopher G. Brinton
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis. CoRR (2024)
Aditya Malusare, Vaneet Aggarwal
Improving Molecule Generation and Drug Discovery with a Knowledge-enhanced Generative Model. CoRR (2024)
Bhrij Patel, Wesley A. Suttle, Alec Koppel, Vaneet Aggarwal, Brian M. Sadler, Amrit Singh Bedi, Dinesh Manocha
Global Optimality without Mixing Time Oracles in Average-reward RL via Multi-level Actor-Critic. CoRR (2024)
Debabrata Pal, Deeptej More, Sai Bhargav, Dipesh Tamboli, Vaneet Aggarwal, Biplab Banerjee
Domain Adaptive Few-Shot Open-Set Learning. CoRR (2023)
Guanghui Zhang, Ke Liu, Haibo Hu, Vaneet Aggarwal, Jack Y. B. Lee
Post-Streaming Wastage Analysis - A Data Wastage Aware Framework in Mobile Video Streaming. IEEE Trans. Mob. Comput. 22 (1) (2023)
Dheeraj Peddireddy, Vipul Bansal, Vaneet Aggarwal
Classical simulation of variational quantum classifiers using tensor rings. Appl. Soft Comput. 141 (2023)
Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning. CoRR (2023)
Debanjan Konar, Dheeraj Peddireddy, Vaneet Aggarwal, Bijaya K. Panigrahi
Tensor Ring Optimized Quantum-Enhanced Tensor Neural Networks. CoRR (2023)
Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal
Learning Multiagent Options for Tabular Reinforcement Learning using Factor Graphs. IEEE Trans. Artif. Intell. 4 (5) (2023)
Washim Uddin Mondal, Vaneet Aggarwal
Reinforcement Learning with Delayed, Composite, and Partially Anonymous Reward. Trans. Mach. Learn. Res. 2023 (2023)
Hanhan Zhou, Tian Lan, Vaneet Aggarwal
Value Functions Factorization With Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients. IEEE Trans. Emerg. Top. Comput. Intell. 7 (5) (2023)
Guanghui Zhang, Jie Zhang, Yan Liu, Haibo Hu, Jack Y. B. Lee, Vaneet Aggarwal
Adaptive Video Streaming With Automatic Quality-of-Experience Optimization. IEEE Trans. Mob. Comput. 22 (8) (2023)
Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal
Scalable Multi-agent Skill Discovery based on Kronecker Graphs. CoRR (2023)
Aditya Malusare, Harish Kothandaraman, Dipesh Tamboli, Nadia A. Lanman, Vaneet Aggarwal
Understanding the Natural Language of DNA using Encoder-Decoder Foundation Models with Byte-level Precision. CoRR (2023)
Fares Fourati, Christopher John Quinn, Mohamed-Slim Alouini, Vaneet Aggarwal
Combinatorial Stochastic-Greedy Bandit. CoRR (2023)
Mohammad Pedramfar, Christopher John Quinn, Vaneet Aggarwal
A Unified Approach for Maximizing Continuous DR-submodular Functions. CoRR (2023)
Guanghui Zhang, Jie Zhang, Ke Liu, Jing Guo, Jack Y. B. Lee, Haibo Hu, Vaneet Aggarwal
DUASVS: A Mobile Data Saving Strategy in Short-Form Video Streaming. IEEE Trans. Serv. Comput. 16 (2) (2023)
Washim Uddin Mondal, Vaneet Aggarwal
Reinforcement Learning with Delayed, Composite, and Partially Anonymous Reward. CoRR (2023)
Abhishek K. Umrawal, Vaneet Aggarwal, Christopher J. Quinn
Fractional Budget Allocation for Influence Maximization. CDC (2023)
Mridul Agarwal, Vaneet Aggarwal
Reinforcement Learning for Joint Optimization of Multiple Rewards. J. Mach. Learn. Res. 24 (2023)
Jiayu Chen, Tian Lan, Vaneet Aggarwal
Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Control. ICRA (2023)
Washim Uddin Mondal, Vaneet Aggarwal
Improved Sample Complexity Analysis of Natural Policy Gradient Algorithm with General Parameterization for Infinite Horizon Discounted Reward Markov Decision Processes. CoRR (2023)
Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri
Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global State. CoRR (2023)
Chang-Lin Chen, Christopher G. Brinton, Vaneet Aggarwal
Latency Minimization for Mobile Edge Computing Networks. IEEE Trans. Mob. Comput. 22 (4) (2023)
Xingyu Fu, Fengfeng Zhou, Dheeraj Peddireddy, Zhengyang Kang, Martin Byung-Guk Jun, Vaneet Aggarwal
An finite element analysis surrogate model with boundary oriented graph embedding approach for rapid design. J. Comput. Des. Eng. 10 (3) (2023)
Guanyu Nie, Yididiya Y. Nadew, Yanhui Zhu, Vaneet Aggarwal, Christopher John Quinn
A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback. ICML (2023)
Rooji Jinan, Gaurav Gautam, Parimal Parag, Vaneet Aggarwal
Asymptotic Analysis of Probabilistic Scheduling for Erasure-Coded Heterogeneous Systems. SIGMETRICS Perform. Evaluation Rev. 50 (4) (2023)
Guanyu Nie, Yididiya Y. Nadew, Yanhui Zhu, Vaneet Aggarwal, Christopher John Quinn
A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback. CoRR (2023)
Bhargav Ganguly, Vaneet Aggarwal
Quantum Acceleration of Infinite Horizon Average-Reward Reinforcement Learning. CoRR (2023)
Guangchen Lan, Han Wang, James Anderson, Christopher G. Brinton, Vaneet Aggarwal
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates. NeurIPS (2023)
Bhargav Ganguly, Seyyedali Hosseinalipour, Kwang Taik Kim, Christopher G. Brinton, Vaneet Aggarwal, David J. Love, Mung Chiang
Multi-Edge Server-Assisted Dynamic Federated Learning With an Optimized Floating Aggregation Point. IEEE/ACM Trans. Netw. 31 (6) (2023)
Divija Swetha Gadiraju, V. Lalitha, Vaneet Aggarwal
An Optimization Framework Based on Deep Reinforcement Learning Approaches for Prism Blockchain. IEEE Trans. Serv. Comput. 16 (4) (2023)
Jiayu Chen, Dipesh Tamboli, Tian Lan, Vaneet Aggarwal
Multi-task Hierarchical Adversarial Inverse Reinforcement Learning. ICML (2023)
Fares Fourati, Vaneet Aggarwal, Christopher John Quinn, Mohamed-Slim Alouini
Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback. CoRR (2023)
Jiayu Chen, Vaneet Aggarwal, Tian Lan
A Unified Algorithm Framework for Unsupervised Discovery of Skills based on Determinantal Point Process. NeurIPS (2023)
Debanjan Konar, Aditya Das Sarma, Soham Bhandary, Siddhartha Bhattacharyya, Attila Cangi, Vaneet Aggarwal
A shallow hybrid classical-quantum spiking feedforward neural network for noise-robust image classification. Appl. Soft Comput. 136 (2023)
Chang-Lin Chen, Hanhan Zhou, Jiayu Chen, Mohammad Pedramfar, Vaneet Aggarwal, Tian Lan, Zheqing Zhu, Chi Zhou, Tim Gasser, Pol Mauri Ruiz, Vijay Menon, Neeraj Kumar, Hongbo Dong
Two-tiered Online Optimization of Region-wide Datacenter Resource Allocation via Deep Reinforcement Learning. CoRR (2023)
Guanghui Zhang, Ke Liu, Mengbai Xiao, Bingshu Wang, Vaneet Aggarwal
An Intelligent Learning Approach to Achieve Near-Second Low-Latency Live Video Streaming under Highly Fluctuating Networks. ACM Multimedia (2023)
Mohammad Pedramfar, Vaneet Aggarwal
Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback. CoRR (2023)
Debanjan Konar, Vaneet Aggarwal, Aditya Das Sarma, Soham Bhandary, Siddhratha Bhattacharyya, Attila Cangi
Deep Spiking Quantum Neural Network for Noisy Image Classification. IJCNN (2023)
Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri
Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global State. Trans. Mach. Learn. Res. 2023 (2023)
Dheeraj Peddireddy, Utkarsh Priyam, Vaneet Aggarwal
Noisy Tensor Ring approximation for computing gradients of Variational Quantum Eigensolver for Combinatorial Optimization. CoRR (2023)
Su Wang, Seyyedali Hosseinalipour, Vaneet Aggarwal, Christopher G. Brinton, David J. Love, Weifeng Su, Mung Chiang
Towards Cooperative Federated Learning over Heterogeneous Edge/Fog Networks. CoRR (2023)
Liyang Zhu, Meng Ding, Vaneet Aggarwal, Jinhui Xu, Di Wang
Improved Analysis of Sparse Linear Regression in Local Differential Privacy Model. CoRR (2023)
Fares Fourati, Salma Kharrat, Vaneet Aggarwal, Mohamed-Slim Alouini, Marco Canini
FilFL: Accelerating Federated Learning via Client Filtering. CoRR (2023)
Jiayu Chen, Dipesh Tamboli, Tian Lan, Vaneet Aggarwal
Multi-task Hierarchical Adversarial Inverse Reinforcement Learning. CoRR (2023)
Jiayu Chen, Tian Lan, Vaneet Aggarwal
Hierarchical Deep Counterfactual Regret Minimization. CoRR (2023)
Qinbo Bai, Washim Uddin Mondal, Vaneet Aggarwal
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes. CoRR (2023)
Fanglin Bao, Xueji Wang, Shree Hari Sureshbabu, Gautam Sreekumar, Liping Yang, Vaneet Aggarwal, Vishnu Naresh Boddeti, Zubin Jacob
Heat-assisted detection and ranging. Nat. 619 (7971) (2023)
Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal
On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization. CoRR (2023)
Debabrata Pal, Deeptej More, Sai Bhargav, Dipesh Tamboli, Vaneet Aggarwal, Biplab Banerjee
Domain Adaptive Few-Shot Open-Set Learning. ICCV (2023)
Abhishek K. Umrawal, Christopher J. Quinn, Vaneet Aggarwal
A Community-Aware Framework for Social Influence Maximization. IEEE Trans. Emerg. Top. Comput. Intell. 7 (4) (2023)
Bhargav Ganguly, Yulian Wu, Di Wang, Vaneet Aggarwal
Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning. CoRR (2023)
Hanhan Zhou, Tian Lan, Vaneet Aggarwal
Statistically Efficient Variance Reduction with Double Policy Estimation for Off-Policy Evaluation in Sequence-Modeled Reinforcement Learning. CoRR (2023)
Qinbo Bai, Amrit Singh Bedi, Vaneet Aggarwal
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm. AAAI (2023)
Nan Geng, Qinbo Bai, Chenyi Liu, Tian Lan, Vaneet Aggarwal, Yuan Yang, Mingwei Xu
A Reinforcement Learning Framework for Vehicular Network Routing Under Peak and Average Constraints. IEEE Trans. Veh. Technol. 72 (5) (2023)
Ruibo Wang, Washim Uddin Mondal, Mustafa A. Kishk, Vaneet Aggarwal, Mohamed-Slim Alouini
Terrain-based Coverage Manifold Estimation: Machine Learning, Stochastic Geometry, or Simulation? CoRR (2023)
Chenyi Liu, Vaneet Aggarwal, Tian Lan, Nan Geng, Yuan Yang, Mingwei Xu
Machine Learning for Robust Network Design: A New Perspective. IEEE Commun. Mag. 61 (10) (2023)
Fares Fourati, Vaneet Aggarwal, Christopher J. Quinn, Mohamed-Slim Alouini
Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback. AISTATS (2023)
Guangchen Lan, Han Wang, James Anderson, Christopher G. Brinton, Vaneet Aggarwal
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates. CoRR (2023)
Jiaqi Yao, Ke Liu, Ting Liang, Theophilus A. Benson, Jack Y. B. Lee, Vaneet Aggarwal, Yungang Bao, Mingyu Chen
A Data-Driven Framework for TCP to Achieve Flexible QoS Control in Mobile Data Networks. IWQoS (2023)
Abhishek K. Umrawal, Vaneet Aggarwal
Leveraging the Community Structure of a Social Network for Maximizing the Spread of Influence. SIGMETRICS Perform. Evaluation Rev. 50 (4) (2023)
Mohammad Pedramfar, Christopher J. Quinn, Vaneet Aggarwal
A Unified Approach for Maximizing Continuous DR-submodular Functions. NeurIPS (2023)
Su Wang, Seyyedali Hosseinalipour, Vaneet Aggarwal, Christopher G. Brinton, David J. Love, Weifeng Su, Mung Chiang
Toward Cooperative Federated Learning Over Heterogeneous Edge/Fog Networks. IEEE Commun. Mag. 61 (12) (2023)
Qinbo Bai, Vaneet Aggarwal, Ather Gattami
Provably Sample-Efficient Model-Free Algorithm for MDPs with Peak Constraints. J. Mach. Learn. Res. 24 (2023)
Ahmadreza Moradipari, Mohammad Pedramfar, Modjtaba Shokrian Zini, Vaneet Aggarwal
Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning. NeurIPS (2023)
Mudit Gaur, Vaneet Aggarwal, Mridul Agarwal
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization. ICML (2023)

Vaneet Aggarwal.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Vaneet Aggarwal