On Parameter Tying by Quantization. - Li Chou; Somdeb Sarkhel; Nicholas Ruozzi; Vibhav Gogate (AAAI, 2016)

Automatic Parameter Tying: A New Approach for Regularized Parameter Learning in Markov Networks. - Li Chou; Pracheta Sahoo; Somdeb Sarkhel; Nicholas Ruozzi; Vibhav Gogate (AAAI, 2018)

Dissociation-Based Oblivious Bounds for Weighted Model Counting. - Li Chou; Wolfgang Gatterbauer; Vibhav Gogate (UAI, 2018)

Neighbor Oblivious Learning (NObLe) for Device Localization and Tracking. - Zichang Liu; Li Chou; Anshumali Shrivastava (DATE, 2021)

Efficient and Less Centralized Federated Learning. - Li Chou; Zichang Liu; Zhuang Wang; Anshumali Shrivastava (ECML/PKDD (1), 2021)

Semantically Constrained Memory Allocation (SCMA) for Embedding in Efficient Recommendation Systems. - Aditya Desai; Yanzhou Pan; Kuangyuan Sun; Li Chou; Anshumali Shrivastava (CoRR, 2021)

Random Offset Block Embedding Array (ROBE) for CriteoTB Benchmark MLPerf DLRM Model : 1000× Compression and 2.7× Faster Inference. - Aditya Desai; Li Chou; Anshumali Shrivastava (CoRR, 2021)

One-Pass Diversified Sampling with Application to Terabyte-Scale Genomic Sequence Streams. - Benjamin Coleman; Benito Geordie; Li Chou; Ryan A. Leo Elworth; Todd J. Treangen; Anshumali Shrivastava (ICML, 2022)

Random Offset Block Embedding (ROBE) for compressed embedding tables in deep learning recommendation systems. - Aditya Desai; Li Chou; Anshumali Shrivastava (MLSys, 2022)