Andrey Malevich

14 papers A* 4A 1B 1Journal 8

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	A Scalable and Effective Alternative to Graph Transformers. AAAI Kaan Sancak, Zhigang Hua, Jin Fang, Yan Xie, Andrey Malevich, Bo Long, Muhammed Fatih Balin, Ümit V. Çatalyürek
2025	A	`conf`	Billion-Scale Graph Deep Learning Framework for Ads Recommendation. CIKM Si Zhang, Weilin Cong, Dongqi Fu, Andrey Malevich, Hao Wu, Baichuan Yuan, Xin Zhou, Kaveh Hassani, Zhigang Hua, Austin Derrow-Pinion, Yan Xie, Xuewei Wang, Yinglong Xia, Ning Yao, Vena Li, Sem Park, Bo Long
2025	B	`conf`	Staleness-Based Subgraph Sampling for Training GNNs on Large-Scale Graphs. IEEE Big Data Limei Wang, Si Zhang, Hanqing Zeng, Hao Wu, Zhigang Hua, Kaveh Hassani, Andrey Malevich, Bo Long, Shuiwang Ji
2024	J	`jnl`	A Scalable and Effective Alternative to Graph Transformers. CoRR Kaan Sancak, Zhigang Hua, Jin Fang, Yan Xie, Andrey Malevich, Bo Long, Muhammed Fatih Balin, Ümit V. Çatalyürek
2024	J	`jnl`	Proactive Detection and Calibration of Seasonal Advertisements with Multimodal Large Language Models. CoRR Hamid Eghbalzadeh, Shuai Shao, Saurabh Verma, Venugopal Mani, Hongnan Wang, Jigar Madia, Vitali Karpinchyk, Andrey Malevich
2024	A*	`conf`	VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections. ICLR Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long
2024	J	`jnl`	VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections. CoRR Dongqi Fu, Zhigang Hua, Yan Xie, Jin Fang, Si Zhang, Kaan Sancak, Hao Wu, Andrey Malevich, Jingrui He, Bo Long
2022	J	`jnl`	Decoupling the Depth and Scope of Graph Neural Networks. CoRR Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen
2021	A*	`conf`	Decoupling the Depth and Scope of Graph Neural Networks. NeurIPS Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen
2020	A*	`conf`	The Architectural Implications of Facebook's DNN-Based Personalized Recommendation. HPCA Udit Gupta, Carole-Jean Wu, Xiaodong Wang, Maxim Naumov, Brandon Reagen, David Brooks, Bradford Cottel, Kim M. Hazelwood, Mark Hempstead, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang
2020	J	`jnl`	Time-based Sequence Model for Personalization and Recommendation Systems. CoRR Tigran Ishkhanov, Maxim Naumov, Xianjie Chen, Yan Zhu, Yuan Zhong, Alisson Gusatti Azzolini, Chonglin Sun, Frank Jiang, Andrey Malevich, Liang Xiong
2019	J	`jnl`	Post-Training 4-bit Quantization on Embedding Tables. CoRR Hui Guan, Andrey Malevich, Jiyan Yang, Jongsoo Park, Hector Yuen
2019	J	`jnl`	The Architectural Implications of Facebook's DNN-based Personalized Recommendation. CoRR Udit Gupta, Xiaodong Wang, Maxim Naumov, Carole-Jean Wu, Brandon Reagen, David Brooks, Bradford Cottel, Kim M. Hazelwood, Bill Jia, Hsien-Hsin S. Lee, Andrey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, Xuan Zhang
2018	J	`jnl`	Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications. CoRR Jongsoo Park, Maxim Naumov, Protonu Basu, Summer Deng, Aravind Kalaiah, Daya Shanker Khudia, James Law, Parth Malani, Andrey Malevich, Nadathur Satish, Juan Miguel Pino, Martin Schatz, Alexander Sidorov, Viswanath Sivakumar, Andrew Tulloch, Xiaodong Wang, Yiming Wu, Hector Yuen, Utku Diril, Dmytro Dzhulgakov, Kim M. Hazelwood, Bill Jia, Yangqing Jia, Lin Qiao, Vijay Rao, Nadav Rotem, Sungjoo Yoo, Mikhail Smelyanskiy