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ORCIDRoger Waleffe
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2020 – today
- 2025
[c4]Yongjun He, Roger Waleffe, Zhichao Han, Johnu George, Binhang Yuan
, Zitao Zhang, Yinan Shan, Yang Zhao, Debojyoti Dutta, Theodoros Rekatsinas, Ce Zhang:
MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage. ICDE 2025: 4134-4141- [i11]Roger Waleffe, Devesh Sarda, Jason Mohoney, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Theodoros Rekatsinas, Shivaram Venkataraman:
Armada: Memory-Efficient Distributed Training of Large-Scale Graph Neural Networks. CoRR abs/2502.17846 (2025) - [i10]Yongjun He, Roger Waleffe, Zhichao Han, Johnu George, Binhang Yuan, Zitao Zhang, Yinan Shan, Yang Zhao, Debojyoti Dutta, Theodoros Rekatsinas, Ce Zhang:
MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage. CoRR abs/2504.01506 (2025) - [i9]Felix Abecassis, Anjulie Agrusa, Dong Ahn, Jonah Alben, Stefania Alborghetti, Michael Andersch, Sivakumar Arayandi, Alexis Bjorlin, Aaron Blakeman, Evan Briones, Ian Buck, Bryan Catanzaro, Jinhang Choi, Mike Chrzanowski, Eric Chung, Victor Cui, Steve Dai, Bita Darvish Rouhani, Carlo del Mundo, Deena Donia, Sukru Burc Eryilmaz, Henry Estela, Abhinav Goel, Oleg Goncharov, Yugi Guvvala, Robert Hesse, Russell Hewett, Herbert Hum, Ujval J. Kapasi, Brucek Khailany, Mikail Khona, Nick Knight, Alex Kondratenko, Ronny Krashinsky, Ben Lanir, Simon Layton, Michael Lightstone, Daniel Lo, Paulius Micikevicius, Asit K. Mishra, Tim Moon, Deepak Narayanan, Chao Ni, Abhijit Paithankar, Satish Pasumarthi, Ankit Patel, Mostofa Patwary, Ashwin Poojary, Gargi Prasad, Sweta Priyadarshi, Yigong Qin, Xiaowei Ren, Oleg Rybakov, Charbel Sakr, Sanjeev Satheesh, Stas Sergienko, Pavel Shamis, Kirthi Shankar, Nishant Sharma, Mohammad Shoeybi, Michael Y. Siu, Misha Smelyanskiy, Darko Stosic, Dusan Stosic, Bor-Yiing Su, Frank Sun, Nima Tajbakhsh, Shelby Thomas, Przemek Tredak, Evgeny Tsykunov, Gandhi Vaithilingam, Aditya Vavre, Rangharajan Venkatesan, Roger Waleffe, Qiyu Wan, Hexin Wang, Mengdi Wang, Lizzie Wei, Hao Wu, Evan Wu, Keith Wyss, Ning Xu, Jinze Xue, Charlene Yang, Yujia Zhai, Ruoxi Zhang, Jingyang Zhu, Zhongbo Zhu:
Pretraining Large Language Models with NVFP4. CoRR abs/2509.25149 (2025) - [i8]Amala Sanjay Deshmukh, Kateryna Chumachenko, Tuomas Rintamaki, Matthieu Le, Tyler Poon, Danial Mohseni-Taheri, Ilia Karmanov, Guilin Liu, Jarno Seppänen, Guo Chen, Karan Sapra, Zhiding Yu, Adi Renduchintala, Charles Wang, Peter Jin, Arushi Goel, Mike Ranzinger, Lukas Voegtle, Philipp Fischer, Timo Roman, Wei Ping, Boxin Wang, Zhuolin Yang, Nayeon Lee, Shaokun Zhang, Fuxiao Liu, Zhiqi Li, Di Zhang, Greg Heinrich, Hongxu Yin, Song Han, Pavlo Molchanov, Parth Mannan, Yao Xu, Jane Polak Scowcroft, Tom Balough, Subhashree Radhakrishnan, Paris Zhang, Sean Cha, Ratnesh Kumar, Zaid Pervaiz Bhat, Jian Zhang, Darragh Hanley, Pritam Biswas, Jesse Oliver, Kevin Vasques, Roger Waleffe, Duncan Riach, Oluwatobi Olabiyi, Ameya Sunil Mahabaleshwarkar, Bilal Kartal, Pritam Gundecha, Khanh Nguyen, Alexandre Milesi, Eugene Khvedchenia, Ran Zilberstein, Ofri Masad, Natan Bagrov, Nave Assaf, Tomer Asida, Daniel Afrimi, Amit Zuker, Netanel Haber, Zhiyu Cheng, Jingyu Xin, Di Wu, Nik Spirin, Maryam Moosaei, Roman Ageev, Vanshil Atul Shah, Yuting Wu, Daniel Korzekwa, Unnikrishnan Kizhakkemadam Sreekumar, Wanli Jiang, Padmavathy Subramanian, Alejandra Rico, Sandip Bhaskar, Saeid Motiian, Kedi Wu, Annie Surla, Chia-Chih Chen, Hayden Wolff, Matthew Feinberg, Melissa Corpuz, Marek Wawrzos, Eileen Long, Aastha Jhunjhunwala, Paul Hendricks, Farzan Memarian, Benika Hall, Xin-Yu Wang, David Mosallanezhad, Soumye Singhal, Luis Vega, Katherine Cheung, Krzysztof Pawelec, Michael Evans, Katherine Luna, Jie Lou:
NVIDIA Nemotron Nano V2 VL. CoRR abs/2511.03929 (2025) - 2024
- [j2]Wenqi Jiang, Marco Zeller, Roger Waleffe, Torsten Hoefler, Gustavo Alonso:
Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language Models. Proc. VLDB Endow. 18(1): 42-52 (2024) - [c3]Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas:
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. ICLR 2024 - [i7]Roger Waleffe, Wonmin Byeon, Duncan Riach, Brandon Norick, Vijay Korthikanti, Tri Dao, Albert Gu, Ali Hatamizadeh, Sudhakar Singh, Deepak Narayanan, Garvit Kulshreshtha, Vartika Singh, Jared Casper, Jan Kautz, Mohammad Shoeybi, Bryan Catanzaro:
An Empirical Study of Mamba-based Language Models. CoRR abs/2406.07887 (2024) - [i6]Dong Liu, Roger Waleffe, Meng Jiang, Shivaram Venkataraman:
GraphSnapShot: Graph Machine Learning Acceleration with Fast Storage and Retrieval. CoRR abs/2406.17918 (2024) - 2023
- [c2]Roger Waleffe, Jason Mohoney, Theodoros Rekatsinas, Shivaram Venkataraman:
MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks. EuroSys 2023: 144-161 - [i5]Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas:
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. CoRR abs/2305.18424 (2023) - [i4]Wenqi Jiang, Marco Zeller, Roger Waleffe, Torsten Hoefler, Gustavo Alonso:
Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language Models. CoRR abs/2310.09949 (2023) - 2022
- [i3]Roger Waleffe, Jason Mohoney, Theodoros Rekatsinas, Shivaram Venkataraman:
Marius++: Large-Scale Training of Graph Neural Networks on a Single Machine. CoRR abs/2202.02365 (2022) - 2021
- [j1]Anders Carlsson, Anze Xie, Jason Mohoney, Roger Waleffe, Shanan Peters, Theodoros Rekatsinas, Shivaram Venkataraman:
Demonstration of Marius: Graph Embeddings with a Single Machine. Proc. VLDB Endow. 14(12): 2759-2762 (2021) - [c1]Jason Mohoney, Roger Waleffe, Henry Xu, Theodoros Rekatsinas, Shivaram Venkataraman:
Marius: Learning Massive Graph Embeddings on a Single Machine. OSDI 2021: 533-549 - [i2]Jason Mohoney, Roger Waleffe, Yiheng Xu, Theodoros Rekatsinas, Shivaram Venkataraman:
Learning Massive Graph Embeddings on a Single Machine. CoRR abs/2101.08358 (2021) - 2020
- [i1]Roger Waleffe, Theodoros Rekatsinas:
Principal Component Networks: Parameter Reduction Early in Training. CoRR abs/2006.13347 (2020)
Coauthor Index
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