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ORCIDNilesh Jain
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2020 – today
- 2025
[c17]Yushi Guan, Daniel Kwan, Jean Sebastien Dandurand, Xi Yan, Ruofan Liang, Yuxuan Zhang, Nilesh Jain, Nilesh A. Ahuja, Selvakumar Panneer, Nandita Vijaykumar:
Retri3D: 3D Neural Graphics Representation Retrieval. ICLR 2025- [i18]Nilesh Jain:
Enhancing Data Integrity through Provenance Tracking in Semantic Web Frameworks. CoRR abs/2501.09029 (2025) - [i17]J. Pablo Muñoz, Jinjie Yuan, Nilesh Jain:
MultiPruner: Balanced Structure Removal in Foundation Models. CoRR abs/2501.09949 (2025) - [i16]Yushi Guan, Daniel Kwan, Ruofan Liang, Selvakumar Panneer, Nilesh Jain, Nilesh A. Ahuja, Nandita Vijaykumar:
INRet: A General Framework for Accurate Retrieval of INRs for Shapes. CoRR abs/2501.15722 (2025) - [i15]J. Pablo Muñoz, Jinjie Yuan, Nilesh Jain:
Low-Rank Adapters Meet Neural Architecture Search for LLM Compression. CoRR abs/2501.16372 (2025) - [i14]J. Pablo Muñoz, Jinjie Yuan, Nilesh Jain:
Mamba-Shedder: Post-Transformer Compression for Efficient Selective Structured State Space Models. CoRR abs/2501.17088 (2025) - [i13]Ahmed F. AbouElhamayed, Jordan Dotzel, Yash Akhauri, Chi-Chih Chang, Sameh Gobriel, J. Pablo Muñoz, Vui Seng Chua, Nilesh Jain, Mohamed S. Abdelfattah:
SparAMX: Accelerating Compressed LLMs Token Generation on AMX-powered CPUs. CoRR abs/2502.12444 (2025) - [i12]Gopi Krishna Jha, Sameh Gobriel, Liubov Talamanova, Alexander Kozlov, Nilesh Jain:
KVCrush: Key value cache size-reduction using similarity in head-behaviour. CoRR abs/2503.00022 (2025) - [i11]Yash Akhauri, Ahmed F. AbouElhamayed, Yifei Gao, Chi-Chih Chang, Nilesh Jain, Mohamed S. Abdelfattah:
TokenButler: Token Importance is Predictable. CoRR abs/2503.07518 (2025) - 2024
- [c16]Juan Pablo Muñoz, Yi Zheng, Nilesh Jain:
EFTNAS: Searching for Efficient Language Models in First-Order Weight-Reordered Super-Networks. LREC/COLING 2024: 5596-5608 - [c15]Juan Pablo Muñoz, Jinjie Yuan, Yi Zheng, Nilesh Jain:
LoNAS: Elastic Low-Rank Adapters for Efficient Large Language Models. LREC/COLING 2024: 10760-10776 - [c14]Peixi Xiong
, Michael Kozuch, Nilesh Jain:
Textual-Visual Logic Challenge: Understanding and Reasoning in Text-to-Image Generation. ECCV (5) 2024: 318-334 - [c13]Juan Pablo Muñoz, Jinjie Yuan, Nilesh Jain:
SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models. EMNLP (Findings) 2024: 12817-12832 - [c12]Yi-Chien Lin, Yuyang Chen, Sameh Gobriel, Nilesh Jain, Gopi Krishna Jha, Viktor K. Prasanna:
ARGO: An Auto-Tuning Runtime System for Scalable GNN Training on Multi-Core Processor. IPDPS 2024: 361-372 - [c11]Adrian Zhao, Louis Zhang, Sankeerth Durvasula, Fan Chen, Nilesh Jain, Selvakumar Panneer, Nandita Vijaykumar:
Distributed Training of Neural Radiance Fields: A Performance Characterization. ISPASS 2024: 319-321 - [c10]J. Pablo Muñoz, Jinjie Yuan, Nilesh Jain:
Shears: Unstructured Sparsity with Neural Low-rank Adapter Search. NAACL (Industry Track) 2024: 395-405 - [i10]Yi-Chien Lin, Yuyang Chen, Sameh Gobriel, Nilesh Jain, Gopi Krishna Jha, Viktor K. Prasanna:
ARGO: An Auto-Tuning Runtime System for Scalable GNN Training on Multi-Core Processor. CoRR abs/2402.03671 (2024) - [i9]J. Pablo Muñoz, Jinjie Yuan, Nilesh Jain:
Shears: Unstructured Sparsity with Neural Low-rank Adapter Search. CoRR abs/2404.10934 (2024) - [i8]Juan Pablo Muñoz, Jinjie Yuan, Nilesh Jain:
SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models. CoRR abs/2410.03750 (2024) - [i7]Vui Seng Chua, Yujie Pan, Nilesh Jain:
Post-Training Statistical Calibration for Higher Activation Sparsity. CoRR abs/2412.07174 (2024) - 2023
- [c9]Gopi Krishna Jha, Anthony Thomas, Nilesh Jain, Sameh Gobriel, Tajana Rosing, Ravi R. Iyer:
Mem-Rec: Memory Efficient Recommendation System using Alternative Representation. ACML 2023: 518-533 - [i6]Gopi Krishna Jha, Anthony Thomas, Nilesh Jain, Sameh Gobriel, Tajana Rosing, Ravi Iyer:
Mem-Rec: Memory Efficient Recommendation System using Alternative Representation. CoRR abs/2305.07205 (2023) - 2022
- [c8]Juan Pablo Muñoz, Nikolay Lyalyushkin, Chaunte Willetta Lacewell, Anastasia Senina, Daniel Cummings, Anthony Sarah, Alexander Kozlov, Nilesh Jain:
Automated Super-Network Generation for Scalable Neural Architecture Search. AutoML 2022: 5/1-15 - [c7]Santiago Miret, Vui Seng Chua, Mattias Marder, Mariano Phielipp, Nilesh Jain, Somdeb Majumdar:
Neuroevolution-enhanced multi-objective optimization for mixed-precision quantization. GECCO 2022: 1057-1065 - [c6]Yash Akhauri, Juan Pablo Muñoz, Nilesh Jain, Ravi Iyer:
EZNAS: Evolving Zero-Cost Proxies For Neural Architecture Scoring. NeurIPS 2022 - [i5]Yash Akhauri, J. Pablo Munoz, Nilesh Jain, Ravi Iyer:
Evolving Zero Cost Proxies For Neural Architecture Scoring. CoRR abs/2209.07413 (2022) - [i4]Anthony Thomas, Behnam Khaleghi, Gopi Krishna Jha, Sanjoy Dasgupta, Nageen Himayat, Ravi Iyer, Nilesh Jain, Tajana Rosing:
Streaming Encoding Algorithms for Scalable Hyperdimensional Computing. CoRR abs/2209.09868 (2022) - 2021
- [j2]Ted Shaowang, Nilesh Jain, Dennis Matthews, Sanjay Krishnan:
Declarative Data Serving: The Future of Machine Learning Inference on the Edge. Proc. VLDB Endow. 14(11): 2555-2562 (2021) - [c5]Jainaveen Sundaram, Srivatsa Rangachar Srinivasa, Dileep Kurian, Indranil Chakraborty, Sirisha Rani Kale, Nilesh Jain, Tanay Karnik, Ravi R. Iyer, Anuradha Srinivasan:
A 93 TOPS/Watt Near-Memory Reconfigurable SAD Accelerator for HEVC/AV1/JEM Encoding. DATE 2021: 1400-1403 - [c4]Yuliang Cai, Sumit Mohan, Adithya Niranjan, Nilesh Jain, Alex Cloninger, Srinjoy Das:
A Manifold Learning based Video Prediction approach for Deep Motion Transfer. ICCVW 2021: 4214-4221 - [c3]Srivatsa Srinivasa, Akshay Krishna Ramanathan, Jainaveen Sundaram, Dileep Kurian, Srinivasan Gopal, Nilesh Jain, Anuradha Srinivasan, Ravi R. Iyer, Vijaykrishnan Narayanan, Tanay Karnik:
Trends and Opportunities for SRAM Based In-Memory and Near-Memory Computation. ISQED 2021: 547-552 - [c2]Chaunte Lacewell, Nilesh A. Ahuja, J. Pablo Munoz, Parual Datta, Ragaad AlTarawneh, Vui Seng Chua, Nilesh Jain, Omesh Tickoo, Ravi Iyer:
E2E Visual Analytics: Achieving >10X Edge/Cloud Optimizations. NAS 2021: 1-8 - [i3]Santiago Miret, Vui Seng Chua, Mattias Marder, Mariano Phielipp, Nilesh Jain, Somdeb Majumdar:
Neuroevolution-Enhanced Multi-Objective Optimization for Mixed-Precision Quantization. CoRR abs/2106.07611 (2021) - [i2]Yash Akhauri, Adithya Niranjan, J. Pablo Muñoz, Suvadeep Banerjee, Abhijit Davare, Pasquale Cocchini, Anton A. Sorokin, Ravi Iyer, Nilesh Jain:
RHNAS: Realizable Hardware and Neural Architecture Search. CoRR abs/2106.09180 (2021) - [i1]J. Pablo Muñoz, Nikolay Lyalyushkin, Yash Akhauri, Anastasia Senina, Alexander Kozlov, Nilesh Jain:
Enabling NAS with Automated Super-Network Generation. CoRR abs/2112.10878 (2021)
2010 – 2019
- 2017
- [j1]Vui Seng Chua, Julio Zamora-Esquivel, Anindya Sao Paul, Thawee Techathamnukool, Carlos Flores Fajardo, Nilesh Jain, Omesh Tickoo, Ravi R. Iyer:
Visual IoT: Ultra-Low-Power Processing Architectures and Implications. IEEE Micro 37(6): 52-61 (2017) - 2013
- [c1]Nilesh Jain, Guangdeng Liao, Theodore L. Willke:
GraphBuilder: scalable graph ETL framework. GRADES 2013: 4
Coauthor Index
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