Co-Designing for Transparency: Lessons from Building a Document Organization Tool for the Criminal Justice Domain (EECS-2023-81)
Hellina Hailu Nigatu, Lisa Pickoff-White, John F. Canny and Sarah Chasins

Hallucination Is All You Need: Using Generative Models for Test Time Data Augmentation (EECS-2022-85)
Dhruv Jhamb

Exploring the Effects of View Transforms on Self-Supervised Video Representation Learning Techniques (EECS-2021-140)
Ilian Herzi

AI for HADR: Progress and Opportunities (EECS-2020-233)
Ross Luo, Michael Laielli, Giscard Biamby and Adam Loeffler

A Study of Transfer Learning Methods within Natural Language Processing and Reinforcement Learning (EECS-2020-98)
Shrishti Jeswani

Risk Averse Robust Adversarial Reinforcement Learning (EECS-2019-165)
Xinlei Pan, Daniel Seita, Yang Gao and John Canny

Risk Averse Robust Adversarial Reinforcement Learning (EECS-2019-164)
Xinlei Pan, Daniel Seita, Yang Gao and John Canny

Curriculum Distillation to Teach Playing Atari (EECS-2018-161)
Chen Tang and John F. Canny

BIDViz: Real-time Monitoring and Debugging of Machine Learning Training Processes (EECS-2017-99)
Han Qi, Jingqiu Liu, Xuan Zou and Allen Tang

Building a Distributed, GPU-based Machine Learning Library (EECS-2016-113)
Richard Chiou, James Jia, Pradeep Kalipatnapu and Yiheng Yang

Building a Distributed, GPU-based Machine Learning Library (EECS-2016-112)
James Jia, Pradeep Kalipatnapu and Yiheng Yang

Data Modeling and Interactive Visualization for Advertisement Auction Modeling (EECS-2016-61)
John F. Canny, Biye Jiang, Ryan Casey, Jian Qiao, Tian Liu and Marc Capelo

Building a Distributed, GPU based Machine Learning library (EECS-2016-52)
Pradeep Kalipatnapu, Yiheng Yang, James Jia and Richard Chiou

Implementing a GPU-based Machine Learning Library on Apache Spark (EECS-2016-51)
James Jia, Pradeep Kalipatnapu, Richard Chiou and Yiheng Yang

Fast Parallel SAME Gibbs Sampling on General Discrete Bayesian Networks and Factor Graphs (EECS-2016-39)
Haoyu Chen and John F. Canny

Optimizing Random Forests on GPU (EECS-2014-205)
Derrick Cheng and John F. Canny

High Performance Machine Learning through Codesign and Rooflining (EECS-2014-169)
Huasha Zhao and John F. Canny

ACES: Automatic Evaluation of Coding Style (EECS-2014-77)
Stephanie Rogers, Dan Garcia, John F. Canny, Steven Tang and Daniel Kang

Communication-Efficient Distributed Stochastic Gradient Descent with Butterfly Mixing (EECS-2012-96)
Huasha Zhao and John F. Canny

An Activity Based Approach to Context-Aware Computing (EECS-2008-163)
Tye Lawrence Rattenbury and John F. Canny

Illuminac: Simultaneous Naming and Configuration for Workspace Lighting Control (EECS-2008-119)
Ana Ramirez Chang and John F. Canny

A Dynamic Topic Model for Document Segmentation (EECS-2006-161)
John F. Canny and Tye Lawrence Rattenbury

Ethno-Mining: Integrating Numbers and Words from the Ground Up (EECS-2006-125)
Ryan Aipperspach, Tye Lawrence Rattenbury, Allison Woodruff, Ken Anderson, John F. Canny and Paul Aoki

Practical Private Computation of Vector Addition-Based Functions or: Can Privacy be for Free? (EECS-2006-12)
John F. Canny and Yitao Duan

Efficient Incremental Algorithms for the Sparse Resultant and the Mixed Volume (CSD-94-839)
Ioannis Z. Emiris and John F. Canny

Impulse-based Dynamic Simulation (CSD-94-815)
Brian Mirtich and John F. Canny

MultiPolynomial Resultant Algorithms (CSD-91-632)
Dinesh Manocha and John F. Canny

Implicitizing Rational Parametric Surfaces (CSD-90-592)
Dinesh Manocha and John F. Canny

Rational Curves with Polynomial Parameterization (CSD-90-560)
Dinesh Manocha and John F. Canny

Detecting Cusps and Inflection Points in Curves (CSD-89-549)
Dinesh Manocha and John F. Canny

Robot Motion Planning with Nonholonomic Constraints (M89/13)
Z. Li and John F. Canny

On Motion Planning for Dexterous Manipulation, Part I: The Problem Formulation (M89/12)
Z. Li, John F. Canny and S. Shankar Sastry

Generalized Characteristic Polynomials (CSD-88-440)
John F. Canny

Some Algebraic and Geometric Computations in PSPACE (CSD-88-439)
John F. Canny

Efficiently Computing and Representing Aspect Graphs of Polyhedral Objects (CSD-88-432)
Ziv Gigus, John F. Canny and Raimund Seidel