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ORCIDAlind Khare
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2020 – today
- 2026
[i13]Anish Biswas, Kanishk Goel, Jayashree Mohan, Alind Khare, Anjaly Parayil, Ramachandran Ramjee, Chetan Bansal:
Sutradhara: An Intelligent Orchestrator-Engine Co-design for Tool-based Agentic Inference. CoRR abs/2601.12967 (2026)- [i12]Shraddha Barke, Arnav Goyal, Alind Khare, Avaljot Singh, Suman Nath, Chetan Bansal:
AgentRx: Diagnosing AI Agent Failures from Execution Trajectories. CoRR abs/2602.02475 (2026) - 2025
- [b1]Alind Khare:
Efficient AI Stack: Deployment-Aware Neural Architecture Search and Serving of Deep Neural Networks. Georgia Institute of Technology, Atlanta, GA, USA, 2025 - [j4]Payman Behnam, Alind Khare, Dhruv Garg, Alexey Tumanov:
Toward Weight Sharing Paradigm for Efficient AI: Training and Inference Serving. ACM SIGOPS Oper. Syst. Rev. 59(1): 34-45 (2025) - [j3]Payman Behnam, Uday Kamal, Sanjana Vijay Ganesh, Zhaoyi Li, Michael Jurado, Alind Khare, Igor Fedorov, Gaowen Liu, Alexey Tumanov:
∇QDARTS: Quantization as an Elastic Dimension to Differentiable NAS. Trans. Mach. Learn. Res. 2025 (2025) - [c9]Haoran Qiu
, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca:
ModServe: Modality- and Stage-Aware Resource Disaggregation for Scalable Multimodal Model Serving. SoCC 2025: 817-830 - [c8]Alind Khare, Dhruv Garg, Sukrit Kalra, Snigdha Grandhi, Ion Stoica, Alexey Tumanov:
SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads. NSDI 2025: 739-758 - [i11]Haoran Qiu, Anish Biswas, Zihan Zhao, Jayashree Mohan, Alind Khare, Esha Choukse, Íñigo Goiri, Zeyu Zhang, Haiying Shen, Chetan Bansal, Ramachandran Ramjee, Rodrigo Fonseca:
Towards Efficient Large Multimodal Model Serving. CoRR abs/2502.00937 (2025) - [i10]Shashwat Jaiswal, Shrikara Arun, Anjaly Parayil, Ankur Mallick, Spyros Mastorakis, Alind Khare, Chloe Alverti, Renée St. Amant, Chetan Bansal, Victor Rühle, Josep Torrellas:
Serving Heterogeneous LoRA Adapters in Distributed LLM Inference Systems. CoRR abs/2511.22880 (2025) - 2024
- [c7]Alind Khare, Animesh Agrawal, Aditya Annavajjala, Payman Behnam, Myungjin Lee, Hugo Latapie, Alexey Tumanov:
SuperFedNAS: Cost-Efficient Federated Neural Architecture Search for On-device Inference. ECCV (79) 2024: 161-179 - [c6]Aditya Annavajjala, Alind Khare, Animesh Agrawal, Igor Fedorov, Hugo Latapie, Myungjin Lee, Alexey Tumanov:
DεpS: Delayed ε-Shrinking for Faster Once-for-All Training. ECCV (89) 2024: 315-331 - [i9]Aditya Annavajjala, Alind Khare, Animesh Agrawal, Igor Fedorov, Hugo Latapie, Myungjin Lee, Alexey Tumanov:
DεS: Delayed ε-Shrinking for Faster Once-For-All Training. CoRR abs/2407.06167 (2024) - 2023
- [j2]Payman Behnam, Jianming Tong, Alind Khare, Yangyu Chen, Yue Pan, Pranav Gadikar, Abhimanyu Bambhaniya, Tushar Krishna, Alexey Tumanov:
Hardware-Software Co-Design for Real-Time Latency-Accuracy Navigation in Tiny Machine Learning Applications. IEEE Micro 43(6): 93-101 (2023) - [c5]Payman Behnam, Alexey Tumanov, Tushar Krishna, Pranav Gadikar, Yangyu Chen, Jianming Tong, Yue Pan, Abhimanyu Rajeshkumar Bambhaniya, Alind Khare:
Subgraph Stationary Hardware-Software Inference Co-Design. MLSys 2023 - [i8]Alind Khare, Animesh Agrawal, Myungjin Lee, Alexey Tumanov:
SuperFed: Weight Shared Federated Learning. CoRR abs/2301.10879 (2023) - [i7]Payman Behnam, Jianming Tong, Alind Khare, Yangyu Chen, Yue Pan, Pranav Gadikar, Abhimanyu Rajeshkumar Bambhaniya, Tushar Krishna, Alexey Tumanov:
Subgraph Stationary Hardware-Software Inference Co-Design. CoRR abs/2306.17266 (2023) - [i6]Anshul Ahluwalia, Rohit Das, Payman Behnam, Alind Khare, Pan Li, Alexey Tumanov:
ABKD: Graph Neural Network Compression with Attention-Based Knowledge Distillation. CoRR abs/2310.15938 (2023) - [i5]Alind Khare, Dhruv Garg, Sukrit Kalra, Snigdha Grandhi, Ion Stoica, Alexey Tumanov:
SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads. CoRR abs/2312.16733 (2023) - 2022
- [c4]Yanbo Xu, Alind Khare, Glenn Matlin, Monish Ramadoss, Rishikesan Kamaleswaran, Chao Zhang, Alexey Tumanov:
UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification. NeurIPS 2022 - [i4]Yanbo Xu, Alind Khare, Glenn Matlin, Monish Ramadoss, Rishikesan Kamaleswaran, Chao Zhang, Alexey Tumanov:
UnfoldML: Cost-Aware and Uncertainty-Based Dynamic 2D Prediction for Multi-Stage Classification. CoRR abs/2210.15056 (2022) - 2021
- [c3]Manas Sahni, Shreya Varshini, Alind Khare, Alexey Tumanov:
CompOFA - Compound Once-For-All Networks for Faster Multi-Platform Deployment. ICLR 2021 - [i3]Manas Sahni, Shreya Varshini, Alind Khare, Alexey Tumanov:
CompOFA: Compound Once-For-All Networks for Faster Multi-Platform Deployment. CoRR abs/2104.12642 (2021) - 2020
- [c2]Shenda Hong, Yanbo Xu, Alind Khare, Satria Priambada, Kevin O. Maher, Alaa Aljiffry, Jimeng Sun, Alexey Tumanov:
HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units. KDD 2020: 1614-1624 - [i2]Shenda Hong, Yanbo Xu, Alind Khare, Satria Priambada, Kevin O. Maher, Alaa Aljiffry, Jimeng Sun, Alexey Tumanov:
HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units. CoRR abs/2008.04063 (2020)
2010 – 2019
- 2019
- [i1]Koyel Mukherjee, Alind Khare, Ashish Verma:
A Simple Dynamic Learning Rate Tuning Algorithm For Automated Training of DNNs. CoRR abs/1910.11605 (2019) - 2017
- [j1]Nilay Khare, Alind Khare, Farhan Khan:
HCudaBLAST: an implementation of BLAST on Hadoop and Cuda. J. Big Data 4: 41 (2017) - [c1]Alind Khare, Vikram Goyal, Srikanth Baride, Sushil K. Prasad, Michael McDermott, Dhara Shah:
Distributed Algorithm for High-Utility Subgraph Pattern Mining Over Big Data Platforms. HiPC 2017: 263-272
Coauthor Index
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last updated on 2026-03-13 22:40 CET by the dblp team
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