Felix X. Yu

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 57

Top Topics

Polynomial Kernels

Kronecker Product

Top Venues

Publications

Michal Lukasik, Harikrishna Narasimhan, Aditya Krishna Menon, Felix X. Yu, Sanjiv Kumar
Metric-aware LLM inference. CoRR (2024)
Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix X. Yu, Sanjiv Kumar
Large Language Models with Controllable Working Memory. ACL (Findings) (2023)
Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat, Sashank J. Reddi, Ke Ye, Felix Chern, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers. ICLR (2023)
Cho-Jui Hsieh, Si Si, Felix X. Yu, Inderjit S. Dhillon
Automatic Engineering of Long Prompts. CoRR (2023)
Si Si, Felix X. Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar
Serving Graph Compression for Graph Neural Networks. ICLR (2023)
Renat Aksitov, Sobhan Miryoosefi, Zonglin Li, Daliang Li, Sheila Babayan, Kavya Kopparapu, Zachary Fisher, Ruiqi Guo, Sushant Prakash, Pranesh Srinivasan, Manzil Zaheer, Felix X. Yu, Sanjiv Kumar
ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent. CoRR (2023)
Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix X. Yu
SpecTr: Fast Speculative Decoding via Optimal Transport. NeurIPS (2023)
Ziteng Sun, Ananda Theertha Suresh, Jae Hun Ro, Ahmad Beirami, Himanshu Jain, Felix X. Yu
SpecTr: Fast Speculative Decoding via Optimal Transport. CoRR (2023)
Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar
Preserving In-Context Learning ability in Large Language Model Fine-tuning. CoRR (2022)
Zonglin Li, Chong You, Srinadh Bhojanapalli, Daliang Li, Ankit Singh Rawat, Sashank J. Reddi, Ke Ye, Felix X. Chern, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar
Large Models are Parsimonious Learners: Activation Sparsity in Trained Transformers. CoRR (2022)
Jianyu Wang, Hang Qi, Ankit Singh Rawat, Sashank J. Reddi, Sagar Waghmare, Felix X. Yu, Gauri Joshi
FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients. CoRR (2022)
Ananda Theertha Suresh, Ziteng Sun, Jae Ro, Felix X. Yu
Correlated Quantization for Distributed Mean Estimation and Optimization. ICML (2022)
Daliang Li, Ankit Singh Rawat, Manzil Zaheer, Xin Wang, Michal Lukasik, Andreas Veit, Felix X. Yu, Sanjiv Kumar
Large Language Models with Controllable Working Memory. CoRR (2022)
Ananda Theertha Suresh, Ziteng Sun, Jae Hun Ro, Felix X. Yu
Correlated quantization for distributed mean estimation and optimization. CoRR (2022)
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
A Field Guide to Federated Optimization. CoRR (2021)
Sashank J. Reddi, Rama Kumar Pasumarthi, Aditya Krishna Menon, Ankit Singh Rawat, Felix X. Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar
RankDistil: Knowledge Distillation for Ranking. AISTATS (2021)
Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces. ICML (2021)
Ankit Singh Rawat, Aditya Krishna Menon, Wittawat Jitkrittum, Sadeep Jayasumana, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
Disentangling Sampling and Labeling Bias for Learning in Large-Output Spaces. CoRR (2021)
Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Ting Chen, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi (Jay) Kang, Evan Ettinger
Self-supervised Learning for Large-scale Item Recommendations. CIKM (2021)
Wittawat Jitkrittum, Michal Lukasik, Ananda Theertha Suresh, Felix X. Yu, Gang Wang
HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation. CoRR (2021)
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14 (1-2) (2021)
Chen Zhu, Ankit Singh Rawat, Manzil Zaheer, Srinadh Bhojanapalli, Daliang Li, Felix X. Yu, Sanjiv Kumar
Modifying Memories in Transformer Models. CoRR (2020)
Felix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Federated Learning with Only Positive Labels. ICML (2020)
Ankit Singh Rawat, Aditya Krishna Menon, Andreas Veit, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
Doubly-stochastic mining for heterogeneous retrieval. CoRR (2020)
Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi Kang, Evan Ettinger
Self-supervised Learning for Deep Models in Recommendations. CoRR (2020)
Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix X. Yu, Sanjiv Kumar
Semantic Label Smoothing for Sequence to Sequence Problems. EMNLP (1) (2020)
Yuhan Liu, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Michael Riley
Learning discrete distributions: user vs item-level privacy. NeurIPS (2020)
Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar
Pre-training Tasks for Embedding-based Large-scale Retrieval. CoRR (2020)
Michal Lukasik, Himanshu Jain, Aditya Krishna Menon, Seungyeon Kim, Srinadh Bhojanapalli, Felix X. Yu, Sanjiv Kumar
Semantic Label Smoothing for Sequence to Sequence Problems. CoRR (2020)
Felix X. Yu, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar
Federated Learning with Only Positive Labels. CoRR (2020)
Yuhan Liu, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Michael Riley
Learning discrete distributions: user vs item-level privacy. CoRR (2020)
Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar
Pre-training Tasks for Embedding-based Large-scale Retrieval. ICLR (2020)
Venkatadheeraj Pichapati, Ananda Theertha Suresh, Felix X. Yu, Sashank J. Reddi, Sanjiv Kumar
AdaCliP: Adaptive Clipping for Private SGD. CoRR (2019)
Sashank J. Reddi, Satyen Kale, Felix X. Yu, Daniel Niels Holtmann-Rice, Jiecao Chen, Sanjiv Kumar
Stochastic Negative Mining for Learning with Large Output Spaces. AISTATS (2019)
Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao
Advances and Open Problems in Federated Learning. CoRR (2019)
Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar
Sampled Softmax with Random Fourier Features. CoRR (2019)
Ankit Singh Rawat, Jiecao Chen, Felix X. Yu, Ananda Theertha Suresh, Sanjiv Kumar
Sampled Softmax with Random Fourier Features. NeurIPS (2019)
Shanshan Wu, Alex Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling. ICML (2019)
Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, Brendan McMahan
cpSGD: Communication-efficient and differentially-private distributed SGD. NeurIPS (2018)
Sashank J. Reddi, Satyen Kale, Felix X. Yu, Daniel N. Holtmann-Rice, Jiecao Chen, Sanjiv Kumar
Stochastic Negative Mining for Learning with Large Output Spaces. CoRR (2018)
Ian En-Hsu Yen, Satyen Kale, Felix X. Yu, Daniel Niels Holtmann-Rice, Sanjiv Kumar, Pradeep Ravikumar
Loss Decomposition for Fast Learning in Large Output Spaces. ICML (2018)
Naman Agarwal, Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan
cpSGD: Communication-efficient and differentially-private distributed SGD. CoRR (2018)
Xu Zhang, Felix X. Yu, Svebor Karaman, Wei Zhang, Shih-Fu Chang
Heated-Up Softmax Embedding. CoRR (2018)
Shanshan Wu, Alexandros G. Dimakis, Sujay Sanghavi, Felix X. Yu, Daniel Niels Holtmann-Rice, Dmitry Storcheus, Afshin Rostamizadeh, Sanjiv Kumar
The Sparse Recovery Autoencoder. CoRR (2018)
Xu Zhang, Felix X. Yu, Svebor Karaman, Shih-Fu Chang
Learning Discriminative and Transformation Covariant Local Feature Detectors. CVPR (2017)
Shankar Kumar, Michael Nirschl, Daniel Niels Holtmann-Rice, Hank Liao, Ananda Theertha Suresh, Felix X. Yu
Lattice rescoring strategies for long short term memory language models in speech recognition. ASRU (2017)
Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar, H. Brendan McMahan
Distributed Mean Estimation with Limited Communication. ICML (2017)
Xiang Wu, Ruiqi Guo, Ananda Theertha Suresh, Sanjiv Kumar, Daniel N. Holtmann-Rice, David Simcha, Felix X. Yu
Multiscale Quantization for Fast Similarity Search. NIPS (2017)
Xu Zhang, Felix X. Yu, Sanjiv Kumar, Shih-Fu Chang
Learning Spread-Out Local Feature Descriptors. ICCV (2017)
Felix X. Yu, Aditya Bhaskara, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang
On Binary Embedding using Circulant Matrices. J. Mach. Learn. Res. 18 (2017)
Shankar Kumar, Michael Nirschl, Daniel N. Holtmann-Rice, Hank Liao, Ananda Theertha Suresh, Felix X. Yu
Lattice Rescoring Strategies for Long Short Term Memory Language Models in Speech Recognition. CoRR (2017)
Xu Zhang, Felix X. Yu, Sanjiv Kumar, Shih-Fu Chang
Learning Spread-out Local Feature Descriptors. CoRR (2017)
Bingchen Gong, Brendan Jou, Felix X. Yu, Shih-Fu Chang
Tamp: A Library for Compact Deep Neural Networks with Structured Matrices. ACM Multimedia (2016)
Felix X. Yu, Ananda Theertha Suresh, Krzysztof Marcin Choromanski, Daniel N. Holtmann-Rice, Sanjiv Kumar
Orthogonal Random Features. NIPS (2016)
Ananda Theertha Suresh, Felix X. Yu, H. Brendan McMahan, Sanjiv Kumar
Distributed Mean Estimation with Limited Communication. CoRR (2016)
Jakub Konecný, H. Brendan McMahan, Felix X. Yu, Peter Richtárik, Ananda Theertha Suresh, Dave Bacon
Federated Learning: Strategies for Improving Communication Efficiency. CoRR (2016)
Felix X. Yu, Ananda Theertha Suresh, Krzysztof Choromanski, Daniel N. Holtmann-Rice, Sanjiv Kumar
Orthogonal Random Features. CoRR (2016)
Yu Cheng, Felix X. Yu, Rogério Schmidt Feris, Sanjiv Kumar, Alok N. Choudhary, Shih-Fu Chang
An Exploration of Parameter Redundancy in Deep Networks with Circulant Projections. ICCV (2015)
Xu Zhang, Felix X. Yu, Shih-Fu Chang, Shengjin Wang
Deep Transfer Network: Unsupervised Domain Adaptation. CoRR (2015)
Xu Zhang, Felix X. Yu, Ruiqi Guo, Sanjiv Kumar, Shengjin Wang, Shih-Fu Chang
Fast Orthogonal Projection Based on Kronecker Product. ICCV (2015)
Felix X. Yu, Aditya Bhaskara, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang
On Binary Embedding using Circulant Matrices. CoRR (2015)
Yu Cheng, Felix X. Yu, Rogério Schmidt Feris, Sanjiv Kumar, Alok N. Choudhary, Shih-Fu Chang
Fast Neural Networks with Circulant Projections. CoRR (2015)
Jeffrey Pennington, Felix X. Yu, Sanjiv Kumar
Spherical Random Features for Polynomial Kernels. NIPS (2015)
Felix X. Yu, Sanjiv Kumar, Henry A. Rowley, Shih-Fu Chang
Compact Nonlinear Maps and Circulant Extensions. CoRR (2015)
Kuan-Ting Lai, Felix X. Yu, Ming-Syan Chen, Shih-Fu Chang
Video Event Detection by Inferring Temporal Instance Labels. CVPR (2014)
Subhabrata Bhattacharya, Felix X. Yu, Shih-Fu Chang
Minimally Needed Evidence for Complex Event Recognition in Unconstrained Videos. ICMR (2014)
Tao Chen, Felix X. Yu, Jiawei Chen, Yin Cui, Yan-Ying Chen, Shih-Fu Chang
Object-Based Visual Sentiment Concept Analysis and Application. ACM Multimedia (2014)
Felix X. Yu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
On Learning with Label Proportions. CoRR (2014)
Felix X. Yu, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang
Circulant Binary Embedding. CoRR (2014)
Felix X. Yu, Liangliang Cao, Michele Merler, Noel C. F. Codella, Tao Chen, John R. Smith, Shih-Fu Chang
Modeling Attributes from Category-Attribute Proportions. ACM Multimedia (2014)
Felix X. Yu, Sanjiv Kumar, Yunchao Gong, Shih-Fu Chang
Circulant Binary Embedding. ICML (2014)
Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
$\propto$SVM for learning with label proportions. CoRR (2013)
Felix X. Yu, Liangliang Cao, Rogério Schmidt Feris, John R. Smith, Shih-Fu Chang
Designing Category-Level Attributes for Discriminative Visual Recognition. CVPR (2013)
Felix X. Yu, Dong Liu, Sanjiv Kumar, Tony Jebara, Shih-Fu Chang
\(\propto\)SVM for Learning with Label Proportions. ICML (3) (2013)
Lisa M. Brown, Liangliang Cao, Chih-Fu Chang, Yu Cheng, Alok N. Choudhary, Noel Codella, Courtenay V. Cotton, Dan Ellis, Quanfu Fan, Rogério Schmidt Feris, Leiguang Gong, Matthew L. Hill, Gang Hua, John R. Kender, Michele Merler, Yadong Mu, Sharath Pankanti, John R. Smith, Felix X. Yu
IBM Research and Columbia University TRECVID-2013 Multimedia Event Detection (MED), Multimedia Event Recounting (MER), Surveillance Event Detection (SED), and Semantic Indexing (SIN) Systems. TRECVID (2013)
Rongrong Ji, Felix X. Yu, Tongtao Zhang, Shih-Fu Chang
Active query sensing: Suggesting the best query view for mobile visual search. ACM Trans. Multim. Comput. Commun. Appl. 8 (S3) (2012)
Liangliang Cao, Shih-Fu Chang, Noel Codella, Courtenay V. Cotton, Dan Ellis, Leiguang Gong, Matthew L. Hill, Gang Hua, John R. Kender, Michele Merler, Yadong Mu, John R. Smith, Felix X. Yu
IBM Research and Columbia University TRECVID-2012 Multimedia Event Detection (MED), Multimedia Event Recounting (MER), and Semantic Indexing (SIN) Systems. TRECVID (2012)
Felix X. Yu, Rongrong Ji, Ming-Hen Tsai, Guangnan Ye, Shih-Fu Chang
Weak attributes for large-scale image retrieval. CVPR (2012)
Felix X. Yu
Intelligent query formulation for mobile visual search. ACM Multimedia (2011)
Felix X. Yu, Rongrong Ji, Tongtao Zhang, Shih-Fu Chang
A mobile location search system with active query sensing. ACM Multimedia (2011)
Felix X. Yu, Rongrong Ji, Shih-Fu Chang
Active query sensing for mobile location search. ACM Multimedia (2011)