Li Chou

Publication Activity (10 Years)

Years Active: 2016-2022
Publications (10 Years): 11

Top Topics

Probabilistic Inference

Satisfiability Testing

Markov Networks

Recommendation Systems

Top Venues

Publications

Benjamin Coleman, Benito Geordie, Li Chou, Ryan A. Leo Elworth, Todd J. Treangen, Anshumali Shrivastava
One-Pass Diversified Sampling with Application to Terabyte-Scale Genomic Sequence Streams. ICML (2022)
Aditya Desai, Li Chou, Anshumali Shrivastava
Random Offset Block Embedding (ROBE) for compressed embedding tables in deep learning recommendation systems. MLSys (2022)
Aditya Desai, Li Chou, Anshumali Shrivastava
Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000× Compression and 2.7× Faster Inference. CoRR (2021)
Li Chou, Zichang Liu, Zhuang Wang, Anshumali Shrivastava
Efficient and Less Centralized Federated Learning. ECML/PKDD (1) (2021)
Zichang Liu, Li Chou, Anshumali Shrivastava
Neighbor Oblivious Learning (NObLe) for Device Localization and Tracking. DATE (2021)
Li Chou, Zichang Liu, Zhuang Wang, Anshumali Shrivastava
Efficient and Less Centralized Federated Learning. CoRR (2021)
Aditya Desai, Yanzhou Pan, Kuangyuan Sun, Li Chou, Anshumali Shrivastava
Semantically Constrained Memory Allocation (SCMA) for Embedding in Efficient Recommendation Systems. CoRR (2021)
Zichang Liu, Li Chou, Anshumali Shrivastava
Neighbor Oblivious Learning (NObLe) for Device Localization and Tracking. CoRR (2020)
Li Chou, Wolfgang Gatterbauer, Vibhav Gogate
Dissociation-Based Oblivious Bounds for Weighted Model Counting. UAI (2018)
Li Chou, Pracheta Sahoo, Somdeb Sarkhel, Nicholas Ruozzi, Vibhav Gogate
Automatic Parameter Tying: A New Approach for Regularized Parameter Learning in Markov Networks. AAAI (2018)
Li Chou, Somdeb Sarkhel, Nicholas Ruozzi, Vibhav Gogate
On Parameter Tying by Quantization. AAAI (2016)