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ORCIDVaneet Aggarwal
Person information
- affiliation: Purdue University, West Lafayette, IN, USA
- affiliation: King Abdulaziz University, Jeddah, Saudi Arabia
- affiliation (2018 - 2019): IISc, Bangalore, India
- affiliation (2013 - 2014): Columbia University, New York, NY, USA
- affiliation (2010 - 2014): AT&T Labs-Research, Florham Park, NJ, USA
- affiliation (PhD 2010): Princeton University, NJ, USA
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2020 – today
- 2023
[j136]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: 110099 (2023)- [j135]Dheeraj Peddireddy, Vipul Bansal, Vaneet Aggarwal:
Classical simulation of variational quantum classifiers using tensor rings. Appl. Soft Comput. 141: 110308 (2023) - [j134]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): 1026-1046 (2023) - [j133]Mridul Agarwal, Vaneet Aggarwal:
Reinforcement Learning for Joint Optimization of Multiple Rewards. J. Mach. Learn. Res. 24: 49:1-49:41 (2023) - [j132]Qinbo Bai, Vaneet Aggarwal, Ather Gattami:
Provably Sample-Efficient Model-Free Algorithm for MDPs with Peak Constraints. J. Mach. Learn. Res. 24: 60:1-60:25 (2023) - [j131]Rooji Jinan, Gaurav Gautam, Parimal Parag, Vaneet Aggarwal:
Asymptotic Analysis of Probabilistic Scheduling for Erasure-Coded Heterogeneous Systems. SIGMETRICS Perform. Evaluation Rev. 50(4): 8-10 (2023) - [j130]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): 17-19 (2023) - [j129]Abhishek K. Umrawal, Christopher J. Quinn, Vaneet Aggarwal:
A Community-Aware Framework for Social Influence Maximization. IEEE Trans. Emerg. Top. Comput. Intell. 7(4): 1253-1262 (2023) - [j128]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): 389-401 (2023) - [j127]Chang-Lin Chen, Christopher G. Brinton, Vaneet Aggarwal:
Latency Minimization for Mobile Edge Computing Networks. IEEE Trans. Mob. Comput. 22(4): 2233-2247 (2023) - [j126]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): 4456-4470 (2023) - [j125]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): 1066-1078 (2023) - [j124]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): 2451-2461 (2023) - [j123]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): 6753-6764 (2023) - [c120]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: 6737-6744 - [c119]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: 7455-7471 - [c118]Jiayu Chen, Dipesh Tamboli, Tian Lan, Vaneet Aggarwal:
Multi-task Hierarchical Adversarial Inverse Reinforcement Learning. ICML 2023: 4895-4920 - [c117]Mudit Gaur, Vaneet Aggarwal, Mridul Agarwal:
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization. ICML 2023: 11013-11049 - [c116]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: 26166-26198 - [c115]Jiayu Chen, Tian Lan, Vaneet Aggarwal:
Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Control. ICRA 2023: 5902-5908 - [c114]Debanjan Konar, Vaneet Aggarwal, Aditya Das Sarma, Soham Bhandary, Siddhratha Bhattacharyya, Attila Cangi:
Deep Spiking Quantum Neural Network for Noisy Image Classification. IJCNN 2023: 1-10 - [c113]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: 1-11 - [i165]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 abs/2301.06889 (2023) - [i164]Yulian Wu, Chaowen Guan, Vaneet Aggarwal, Di Wang:
Quantum Heavy-tailed Bandits. CoRR abs/2301.09680 (2023) - [i163]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 abs/2301.13326 (2023) - [i162]Fares Fourati, Vaneet Aggarwal, Christopher John Quinn, Mohamed-Slim Alouini:
Randomized Greedy Learning for Non-monotone Stochastic Submodular Maximization Under Full-bandit Feedback. CoRR abs/2302.01324 (2023) - [i161]Fares Fourati, Salma Kharrat, Vaneet Aggarwal, Mohamed-Slim Alouini, Marco Canini:
FilFL: Accelerating Federated Learning via Client Filtering. CoRR abs/2302.06599 (2023) - [i160]Bhargav Ganguly, Yulian Wu, Di Wang, Vaneet Aggarwal:
Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning. CoRR abs/2302.08617 (2023) - [i159]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 abs/2303.08361 (2023) - [i158]Mohammad Pedramfar, Vaneet Aggarwal:
Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback. CoRR abs/2303.13604 (2023) - [i157]Washim Uddin Mondal, Vaneet Aggarwal:
Reinforcement Learning with Delayed, Composite, and Partially Anonymous Reward. CoRR abs/2305.02527 (2023) - [i156]Jiayu Chen, Dipesh Tamboli, Tian Lan, Vaneet Aggarwal:
Multi-task Hierarchical Adversarial Inverse Reinforcement Learning. CoRR abs/2305.12633 (2023) - [i155]Mohammad Pedramfar, Christopher John Quinn, Vaneet Aggarwal:
A Unified Approach for Maximizing Continuous DR-submodular Functions. CoRR abs/2305.16671 (2023) - [i154]Jiayu Chen, Tian Lan, Vaneet Aggarwal:
Hierarchical Deep Counterfactual Regret Minimization. CoRR abs/2305.17327 (2023) - [i153]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. CoRR abs/2305.19153 (2023) - [i152]Mudit Gaur, Amrit Singh Bedi, Di Wang, Vaneet Aggarwal:
On the Global Convergence of Natural Actor-Critic with Two-layer Neural Network Parametrization. CoRR abs/2306.10486 (2023) - [i151]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 abs/2306.17054 (2023) - [i150]Dheeraj Peddireddy, Utkarsh Priyam, Vaneet Aggarwal:
Noisy Tensor Ring approximation for computing gradients of Variational Quantum Eigensolver for Combinatorial Optimization. CoRR abs/2307.03884 (2023) - [i149]Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal:
Scalable Multi-agent Skill Discovery based on Kronecker Graphs. CoRR abs/2307.11629 (2023) - [i148]Hanhan Zhou, Tian Lan, Vaneet Aggarwal:
Statistically Efficient Variance Reduction with Double Policy Estimation for Off-Policy Evaluation in Sequence-Modeled Reinforcement Learning. CoRR abs/2308.14897 (2023) - [i147]Qinbo Bai, Washim Uddin Mondal, Vaneet Aggarwal:
Regret Analysis of Policy Gradient Algorithm for Infinite Horizon Average Reward Markov Decision Processes. CoRR abs/2309.01922 (2023) - 2022
- [j122]Mridul Agarwal, Vaneet Aggarwal, Arnob Ghosh, Nilay Tiwari:
Reinforcement Learning for Mean-Field Game. Algorithms 15(3): 73 (2022) - [j121]Yimeng Wang, Mridul Agarwal, Tian Lan, Vaneet Aggarwal:
Learning-Based Online QoE Optimization in Multi-Agent Video Streaming. Algorithms 15(7): 227 (2022) - [j120]Qinbo Bai, Mridul Agarwal, Vaneet Aggarwal:
Joint Optimization of Concave Scalarized Multi-Objective Reinforcement Learning with Policy Gradient Based Algorithm. J. Artif. Intell. Res. 74: 1565-1597 (2022) - [j119]Washim Uddin Mondal, Mridul Agarwal, Vaneet Aggarwal, Satish V. Ukkusuri:
On the Approximation of Cooperative Heterogeneous Multi-Agent Reinforcement Learning (MARL) using Mean Field Control (MFC). J. Mach. Learn. Res. 23: 129:1-129:46 (2022) - [j118]Mridul Agarwal, Vaneet Aggarwal, Kamyar Azizzadenesheli:
Multi-Agent Multi-Armed Bandits with Limited Communication. J. Mach. Learn. Res. 23: 212:1-212:24 (2022) - [j117]Washim Uddin Mondal, Praful D. Mankar, Goutam Das, Vaneet Aggarwal, Satish V. Ukkusuri:
Deep Learning-Based Coverage and Rate Manifold Estimation in Cellular Networks. IEEE Trans. Cogn. Commun. Netw. 8(4): 1706-1715 (2022) - [j116]Trevor Bonjour, Marina Haliem, Aala Oqab Alsalem, Shilpa Thomas, Hongyu Li, Vaneet Aggarwal, Mayank Kejriwal, Bharat K. Bhargava:
Decision Making in Monopoly Using a Hybrid Deep Reinforcement Learning Approach. IEEE Trans. Emerg. Top. Comput. Intell. 6(6): 1335-1344 (2022) - [j115]Guoyang Zhou, Vaneet Aggarwal, Ming Yin, Denny Yu:
A Computer Vision Approach for Estimating Lifting Load Contributors to Injury Risk. IEEE Trans. Hum. Mach. Syst. 52(2): 207-219 (2022) - [j114]Xingyu Fu, Dheeraj Peddireddy, Vaneet Aggarwal, Martin Byung-Guk Jun:
Improved Dexel Representation: A 3-D CNN Geometry Descriptor for Manufacturing CAD. IEEE Trans. Ind. Informatics 18(9): 5882-5892 (2022) - [j113]Marina Haliem, Vaneet Aggarwal, Bharat K. Bhargava:
AdaPool: A Diurnal-Adaptive Fleet Management Framework Using Model-Free Deep Reinforcement Learning and Change Point Detection. IEEE Trans. Intell. Transp. Syst. 23(3): 2471-2481 (2022) - [j112]Kaushik Manchella, Marina Haliem, Vaneet Aggarwal, Bharat K. Bhargava:
PassGoodPool: Joint Passengers and Goods Fleet Management With Reinforcement Learning Aided Pricing, Matching, and Route Planning. IEEE Trans. Intell. Transp. Syst. 23(4): 3866-3877 (2022) - [j111]Ashutosh Singh, Abubakr O. Al-Abbasi, Vaneet Aggarwal:
A Distributed Model-Free Algorithm for Multi-Hop Ride-Sharing Using Deep Reinforcement Learning. IEEE Trans. Intell. Transp. Syst. 23(7): 8595-8605 (2022) - [j110]Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal:
Concave Utility Reinforcement Learning with Zero-Constraint Violations. Trans. Mach. Learn. Res. 2022 (2022) - [j109]Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri:
On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learning. Trans. Mach. Learn. Res. 2022 (2022) - [j108]Seyyedali Hosseinalipour, Sheikh Shams Azam, Christopher G. Brinton, Nicolò Michelusi, Vaneet Aggarwal, David J. Love, Huaiyu Dai:
Multi-Stage Hybrid Federated Learning Over Large-Scale D2D-Enabled Fog Networks. IEEE/ACM Trans. Netw. 30(4): 1569-1584 (2022) - [j107]Abubakr O. Al-Abbasi, Vaneet Aggarwal:
Joint Information Freshness and Completion Time Optimization for Vehicular Networks. IEEE Trans. Serv. Comput. 15(2): 1118-1129 (2022) - [j106]Amrit Singh Bedi, Ketan Rajawat, Vaneet Aggarwal, Alec Koppel:
Escaping Saddle Points for Successive Convex Approximation. IEEE Trans. Signal Process. 70: 307-321 (2022) - [j105]Mahadesh Panju, Ramkumar Raghu, Vinod Sharma, Vaneet Aggarwal, Ramachandran Rajesh:
Queueing Theoretic Models for Uncoded and Coded Multicast Wireless Networks With Caches. IEEE Trans. Wirel. Commun. 21(2): 1257-1271 (2022) - [c112]Qinbo Bai, Amrit Singh Bedi, Mridul Agarwal, Alec Koppel, Vaneet Aggarwal:
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Primal-Dual Approach. AAAI 2022: 3682-3689 - [c111]Mridul Agarwal, Vaneet Aggarwal, Tian Lan:
Multi-Objective Reinforcement Learning with Non-Linear Scalarization. AAMAS 2022: 9-17 - [c110]Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal:
Multi-agent Covering Option Discovery through Kronecker Product of Factor Graphs. AAMAS 2022: 1572-1574 - [c109]Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, Vaneet Aggarwal:
Convergence Rates of Average-Reward Multi-agent Reinforcement Learning via Randomized Linear Programming. CDC 2022: 4545-4552 - [c108]Anis Elgabli, Chaouki Ben Issaid, Amrit Singh Bedi, Ketan Rajawat, Mehdi Bennis, Vaneet Aggarwal:
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning. ICML 2022: 5861-5877 - [c107]Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal:
Scalable Multi-agent Covering Option Discovery based on Kronecker Graphs. NeurIPS 2022 - [c106]Hanhan Zhou, Tian Lan, Vaneet Aggarwal:
PAC: Assisted Value Factorization with Counterfactual Predictions in Multi-Agent Reinforcement Learning. NeurIPS 2022 - [c105]Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal:
Regret guarantees for model-based reinforcement learning with long-term average constraints. UAI 2022: 22-31 - [c104]Trevor Bonjour, Vaneet Aggarwal, Bharat K. Bhargava:
Information theoretic approach to detect collusion in multi-agent games. UAI 2022: 223-232 - [c103]Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri:
Can mean field control (mfc) approximate cooperative multi agent reinforcement learning (marl) with non-uniform interaction? UAI 2022: 1371-1380 - [c102]Guanyu Nie, Mridul Agarwal, Abhishek Kumar Umrawal, Vaneet Aggarwal, Christopher John Quinn:
An explore-then-commit algorithm for submodular maximization under full-bandit feedback. UAI 2022: 1541-1551 - [i146]Hanhan Zhou, Tian Lan, Vaneet Aggarwal:
Value Functions Factorization with Latent State Information Sharing in Decentralized Multi-Agent Policy Gradients. CoRR abs/2201.01247 (2022) - [i145]Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal:
Multi-agent Covering Option Discovery based on Kronecker Product of Factor Graphs. CoRR abs/2201.08227 (2022) - [i144]Dheeraj Peddireddy, Vipul Bansal, Zubin Jacob, Vaneet Aggarwal:
Tensor Ring Parametrized Variational Quantum Circuits for Large Scale Quantum Machine Learning. CoRR abs/2201.08878 (2022) - [i143]Ciyuan Zhang, Su Wang, Vaneet Aggarwal, Borja Peleato:
Coded Caching with Heterogeneous User Profiles. CoRR abs/2201.10646 (2022) - [i142]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. CoRR abs/2202.02947 (2022) - [i141]Washim Uddin Mondal, Praful D. Mankar, Goutam Das, Vaneet Aggarwal, Satish V. Ukkusuri:
Deep Learning based Coverage and Rate Manifold Estimation in Cellular Networks. CoRR abs/2202.06390 (2022) - [i140]Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri:
Can Mean Field Control (MFC) Approximate Cooperative Multi Agent Reinforcement Learning (MARL) with Non-Uniform Interaction? CoRR abs/2203.00035 (2022) - [i139]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. CoRR abs/2203.13950 (2022) - [i138]Qinbo Bai, Amrit Singh Bedi, Vaneet Aggarwal:
Achieving Zero Constraint Violation for Constrained Reinforcement Learning via Conservative Natural Policy Gradient Primal-Dual Algorithm. CoRR abs/2206.05850 (2022) - [i137]Anis Elgabli, Chaouki Ben Issaid, Amrit S. Bedi, Ketan Rajawat, Mehdi Bennis, Vaneet Aggarwal:
FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning. CoRR abs/2206.08829 (2022) - [i136]Hanhan Zhou, Tian Lan, Vaneet Aggarwal:
PAC: Assisted Value Factorisation with Counterfactual Predictions in Multi-Agent Reinforcement Learning. CoRR abs/2206.11420 (2022) - [i135]Abhishek Kumar Umrawal, Vaneet Aggarwal:
A Community-Aware Framework for Social Influence Maximization. CoRR abs/2207.08937 (2022) - [i134]Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri:
On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learning. CoRR abs/2209.03491 (2022) - [i133]Washim Uddin Mondal, Vaneet Aggarwal, Satish V. Ukkusuri:
Mean-Field Approximation of Cooperative Constrained Multi-Agent Reinforcement Learning (CMARL). CoRR abs/2209.07437 (2022) - [i132]Jiayu Chen, Tian Lan, Vaneet Aggarwal:
Hierarchical Adversarial Inverse Reinforcement Learning. CoRR abs/2210.01969 (2022) - [i131]Jiayu Chen, Marina Haliem, Tian Lan, Vaneet Aggarwal:
Multi-agent Deep Covering Option Discovery. CoRR abs/2210.03269 (2022) - [i130]Mudit Gaur, Vaneet Aggarwal, Mridul Agarwal:
On the Global Convergence of Fitted Q-Iteration with Two-layer Neural Network Parametrization. CoRR abs/2211.07675 (2022) - [i129]Bhargav Ganguly, Vaneet Aggarwal:
Online Federated Learning via Non-Stationary Detection and Adaptation amidst Concept Drift. CoRR abs/2211.12578 (2022) - [i128]Jiayu Chen, Vaneet Aggarwal, Tian Lan:
ODPP: A Unified Algorithm Framework for Unsupervised Option Discovery based on Determinantal Point Process. CoRR abs/2212.00211 (2022) - 2021
- [j104]Naimahmed Nesaragi, Shivnarayan Patidar, Vaneet Aggarwal:
Tensor learning of pointwise mutual information from EHR data for early prediction of sepsis. Comput. Biol. Medicine 134: 104430 (2021) - [j103]Md. Masudur Rahman, Mythra V. Balakuntala, Glebys T. Gonzalez, Mridul Agarwal, Upinder Kaur, Vishnunandan L. N. Venkatesh, Natalia Sanchez-Tamayo, Yexiang Xue, Richard M. Voyles, Vaneet Aggarwal, Juan P. Wachs:
SARTRES: a semi-autonomous robot teleoperation environment for surgery. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 9(4): 376-383 (2021) - [j102]Vaneet Aggarwal:
Machine Learning for Communications. Entropy 23(7): 831 (2021) - [j101]Ramkumar Raghu, Mahadesh Panju, Vaneet Aggarwal, Vinod Sharma:
Scheduling and Power Control for Wireless Multicast Systems via Deep Reinforcement Learning. Entropy 23(12): 1555 (2021) - [j100]Vaneet Aggarwal, Tian Lan:
Modeling and Optimization of Latency in Erasure-coded Storage Systems. Found. Trends Commun. Inf. Theory 18(3): 380-525 (2021) - [j99]Vaneet Aggarwal, Tian Lan, Dheeraj Peddireddy:
Preemptive scheduling on unrelated machines with fractional precedence constraints. J. Parallel Distributed Comput. 157: 280-286 (2021) - [j98]Mridul Agarwal, Vaneet Aggarwal:
Blind decision making: Reinforcement learning with delayed observations. Pattern Recognit. Lett. 150: 176-182 (2021) - [j97]Abubakr O. Al-Abbasi, Vaneet Aggarwal, Tian Lan, Yu Xiang, Moo-Ryong Ra, Yih-Farn Chen:
FastTrack: Minimizing Stalls for CDN-Based Over-the-Top Video Streaming Systems. IEEE Trans. Cloud Comput. 9(4): 1453-1466 (2021) - [j96]Anis Elgabli, Jihong Park, Amrit Singh Bedi, Chaouki Ben Issaid, Mehdi Bennis, Vaneet Aggarwal:
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning. IEEE Trans. Commun. 69(1): 164-181 (2021) - [j95]Mridul Agarwal, Vaneet Aggarwal, Abhishek K. Umrawal, Christopher J. Quinn:
Stochastic Top K-Subset Bandits with Linear Space and Non-Linear Feedback with Applications to Social Influence Maximization. Trans. Data Sci. 2(4): 38:1-38:39 (2021) - [j94]Kaushik Manchella, Abhishek K. Umrawal, Vaneet Aggarwal:
FlexPool: A Distributed Model-Free Deep Reinforcement Learning Algorithm for Joint Passengers and Goods Transportation. IEEE Trans. Intell. Transp. Syst. 22(4): 2035-2047 (2021) - [j93]Marina Haliem, Ganapathy Mani, Vaneet Aggarwal, Bharat K. Bhargava:
A Distributed Model-Free Ride-Sharing Approach for Joint Matching, Pricing, and Dispatching Using Deep Reinforcement Learning. IEEE Trans. Intell. Transp. Syst. 22(12): 7931-7942 (2021) - [j92]Rutvij H. Jhaveri, Sagar V. Ramani, Gautam Srivastava, Thippa Reddy Gadekallu, Vaneet Aggarwal:
Fault-Resilience for Bandwidth Management in Industrial Software-Defined Networks. IEEE Trans. Netw. Sci. Eng. 8(4): 3129-3139 (2021) - [j91]Ruijiu Mao, Vaneet Aggarwal:
NPSCS: Non-Preemptive Stochastic Coflow Scheduling With Time-Indexed LP Relaxation. IEEE Trans. Netw. Serv. Manag. 18(2): 2377-2387 (2021) - [j90]Vaneet Aggarwal, Tian Lan, Suresh Subramaniam, Maotong Xu:
On the Approximability of Related Machine Scheduling Under Arbitrary Precedence. IEEE Trans. Netw. Serv. Manag. 18(3): 3706-3718 (2021) - [j89]Abubakr O. Al-Abbasi, Vaneet Aggarwal:
VidCloud: Joint Stall and Quality Optimization for Video Streaming over Cloud. ACM Trans. Model. Perform. Evaluation Comput. Syst. 5(4): 17:1-17:32 (2021) - [j88]Ajay Badita, Parimal Parag, Vaneet Aggarwal:
Single-Forking of Coded Subtasks for Straggler Mitigation. IEEE/ACM Trans. Netw. 29(6): 2413-2424 (2021) - [j87]Guanghui Zhang, Jack Y. B. Lee, Ke Liu, Haibo Hu, Vaneet Aggarwal:
A Unified Framework for Flexible Playback Latency Control in Live Video Streaming. IEEE Trans. Parallel Distributed Syst. 32(12): 3024-3037 (2021) - [j86]Yang Zhang, Arnob Ghosh, Vaneet Aggarwal:
Optimized Portfolio Contracts for Bidding the Cloud. IEEE Trans. Serv. Comput. 14(5): 1505-1518 (2021) - [c101]Mridul Agarwal, Vaneet Aggarwal, Abhishek Kumar Umrawal, Christopher J. Quinn:
DART: Adaptive Accept Reject Algorithm for Non-Linear Combinatorial Bandits. AAAI 2021: 6557-6565 - [c100]Alec Koppel, Amrit Singh Bedi, Bhargav Ganguly, Vaneet Aggarwal:
Randomized Linear Programming for Tabular Average-Cost Multi-agent Reinforcement Learning. ACSCC 2021: 1023-1026 - [c99]Mridul Agarwal, Vaneet Aggarwal:
Blind Decision Making: Reinforcement Learning with Delayed Observations. ICAPS 2021: 2-6 - [c98]Jiayu Chen, Abhishek K. Umrawal, Tian Lan, Vaneet Aggarwal:
DeepFreight: A Model-free Deep-reinforcement-learning-based Algorithm for Multi-transfer Freight Delivery. ICAPS 2021: 510-518 - [c97]