Roger Waleffe - RankMe

16 papers A* 3A 1Journal 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	LatentMoE: Toward Optimal Accuracy per FLOP and Parameter in Mixture of Experts. CoRR Venmugil Elango, Nidhi Bhatia, Roger Waleffe, Rasoul Shafipour, Tomer Asida, Abhinav Khattar, Nave Assaf, Maximilian Golub, Joey Guman, Tiyasa Mitra, Ritchie Zhao, Ritika Borkar, Ran Zilberstein, Mostofa Patwary, Mohammad Shoeybi, Bita Rouhani
2025	J	`jnl`	Armada: Memory-Efficient Distributed Training of Large-Scale Graph Neural Networks. CoRR Roger Waleffe, Devesh Sarda, Jason Mohoney, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Theodoros Rekatsinas, Shivaram Venkataraman
2025	A*	`conf`	MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage. ICDE Yongjun He, Roger Waleffe, Zhichao Han, Johnu George, Binhang Yuan, Zitao Zhang, Yinan Shan, Yang Zhao, Debojyoti Dutta, Theodoros Rekatsinas, Ce Zhang
2025	J	`jnl`	MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage. CoRR Yongjun He, Roger Waleffe, Zhichao Han, Johnu George, Binhang Yuan, Zitao Zhang, Yinan Shan, Yang Zhao, Debojyoti Dutta, Theodoros Rekatsinas, Ce Zhang
2024	J	`jnl`	An Empirical Study of Mamba-based Language Models. CoRR 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
2024	J	`jnl`	Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language Models. Proc. VLDB Endow. Wenqi Jiang, Marco Zeller, Roger Waleffe, Torsten Hoefler, Gustavo Alonso
2024	J	`jnl`	GraphSnapShot: Graph Machine Learning Acceleration with Fast Storage and Retrieval. CoRR Dong Liu, Roger Waleffe, Meng Jiang, Shivaram Venkataraman
2024	A*	`conf`	Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. ICLR Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas
2023	J	`jnl`	Chameleon: a Heterogeneous and Disaggregated Accelerator System for Retrieval-Augmented Language Models. CoRR Wenqi Jiang, Marco Zeller, Roger Waleffe, Torsten Hoefler, Gustavo Alonso
2023	A	`conf`	MariusGNN: Resource-Efficient Out-of-Core Training of Graph Neural Networks. EuroSys Roger Waleffe, Jason Mohoney, Theodoros Rekatsinas, Shivaram Venkataraman
2023	J	`jnl`	Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning. CoRR Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos, Konstantinos E. Nikolakakis, Amin Karbasi, Dionysios S. Kalogerias, Nezihe Merve Gürel, Theodoros Rekatsinas
2022	J	`jnl`	Marius++: Large-Scale Training of Graph Neural Networks on a Single Machine. CoRR Roger Waleffe, Jason Mohoney, Theodoros Rekatsinas, Shivaram Venkataraman
2021	J	`jnl`	Demonstration of Marius: Graph Embeddings with a Single Machine. Proc. VLDB Endow. Anders Carlsson, Anze Xie, Jason Mohoney, Roger Waleffe, Shanan Peters, Theodoros Rekatsinas, Shivaram Venkataraman
2021	J	`jnl`	Learning Massive Graph Embeddings on a Single Machine. CoRR Jason Mohoney, Roger Waleffe, Yiheng Xu, Theodoros Rekatsinas, Shivaram Venkataraman
2021	A*	`conf`	Marius: Learning Massive Graph Embeddings on a Single Machine. OSDI Jason Mohoney, Roger Waleffe, Henry Xu, Theodoros Rekatsinas, Shivaram Venkataraman
2020	J	`jnl`	Principal Component Networks: Parameter Reduction Early in Training. CoRR Roger Waleffe, Theodoros Rekatsinas