Packing Shelves with Items that Divide the Shelves' Length: a Case of a Universal Number Partition Problem. - Moshe Dror; James B. Orlin; Michael Zhu (Discret. Math. Algorithms Appl., 2010)

A Practical Algorithm for Topic Modeling with Provable Guarantees. - Sanjeev Arora; Rong Ge 001; Yonatan Halpern; David M. Mimno; Ankur Moitra; David A. Sontag; Yichen Wu; Michael Zhu (ICML (2), 2013)

Camera Network Topology Estimation by Lighting Variation. - Michael Zhu; Anthony R. Dick; Anton van den Hengel (DICTA, 2015)

A Hybrid Approach for Probabilistic Inference using Random Projections. - Michael Zhu; Stefano Ermon (ICML, 2015)

Optimal Kernel Group Transformation for Exploratory Regression Analysis and Graphics. - Pan Chao; Qiming Huang; Michael Zhu (KDD, 2015)

Large-Scale Camera Network Topology Estimation by Lighting Variation. - Michael Zhu; Anthony R. Dick; Anton van den Hengel (ACIVS, 2017)

SPOT: Sparse Optimal Transformations for High Dimensional Variable Selection and Exploratory Regression Analysis. - Qiming Huang; Michael Zhu (KDD, 2017)

Group Additive Structure Identification for Kernel Nonparametric Regression. - Chao Pan; Michael Zhu (NIPS, 2017)

To Prune, or Not to Prune: Exploring the Efficacy of Pruning for Model Compression. - Michael Zhu; Suyog Gupta (ICLR (Workshop), 2018)

Learning topic models - provably and efficiently. - Sanjeev Arora; Rong Ge 001; Yoni Halpern; David M. Mimno; Ankur Moitra; David A. Sontag; Yichen Wu; Michael Zhu (Commun. ACM, 2018)

Sample Adaptive MCMC. - Michael Zhu (NeurIPS, 2019)

Variance Reduction and Quasi-Newton for Particle-Based Variational Inference. - Michael Zhu; Chang Liu 030; Jun Zhu 001 (ICML, 2020)

LB-CNN: Convolutional Neural Network with Latent Binarization for Large Scale Multi-class Classification. - Timothy Reese; Michael Zhu (ICMLA, 2020)

Towards Differentiable Resampling. - Michael Zhu; Kevin Murphy; Rico Jonschkowski (CoRR, 2020)

Multi-level Training and Bayesian Optimization for Economical Hyperparameter Optimization. - Yang Yang; Ke Deng; Michael Zhu (CoRR, 2020)

Recurrent Neural Networks with Mixed Hierarchical Structures for Natural Language Processing. - Zhaoxin Luo; Michael Zhu (IJCNN, 2021)

COVID-19 Vaccine and Social Media: Exploring Emotions and Discussions on Twitter. - Amir Karami; Michael Zhu; Bailey Goldschmidt; Hannah R. Boyajieff; Mahdi M. Najafabadi (CoRR, 2021)

2020 U.S. Presidential Election: Analysis of Female and Male Users on Twitter. - Amir Karami; Spring B. Clark; Anderson Mackenzie; Dorathea Lee; Michael Zhu; Hannah R. Boyajieff; Bailey Goldschmidt (CoRR, 2021)

Using Transformers and Deep Learning with Stance Detection to Forecast Cryptocurrency Price Movement. - Yeonwoo Son; Soham Vohra; Rohit Vakkalagadda; Michael Zhu; Aadvait Hirde; Saurav Kumar; Arjun Rajaram (ICTC, 2022)

Validating the effects of immersion and spatial audio using novel continuous biometric sensor measures for Virtual Reality. - Richard Warp; Michael Zhu; Ivana Kiprijanovska; Jonathan Wiesler; Scot Stafford; Ifigeneia Mavridou (ISMAR Adjunct, 2022)

Recurrent Neural Networks with Mixed Hierarchical Structures and EM Algorithm for Natural Language Processing. - Zhaoxin Luo; Michael Zhu (LREC, 2022)

2020 U.S. presidential election in swing states: Gender differences in Twitter conversations. - Amir Karami; Spring B. Clark; Anderson Mackenzie; Dorathea Lee; Michael Zhu; Hannah R. Boyajieff; Bailey Goldschmidt (Int. J. Inf. Manag. Data Insights, 2022)

Revisiting Cross-Lingual Summarization: A Corpus-based Study and A New Benchmark with Improved Annotation. - Yulong Chen 001; Huajian Zhang; Yijie Zhou; Xuefeng Bai 001; Yueguan Wang; Ming Zhong 005; Jianhao Yan; Yafu Li; Judy Li; Michael Zhu; Yue Zhang 004 (CoRR, 2023)

Cicada: A framework for private non-interactive on-chain auctions and voting. - Noemi Glaeser; István András Seres; Michael Zhu; Joseph Bonneau (IACR Cryptol. ePrint Arch., 2023)

Proving CPU Executions in Small Space. - Vineet Nair; Justin Thaler; Michael Zhu (IACR Cryptol. ePrint Arch., 2025)