| 2023 | ICLR | Noise Is Not the Main Factor Behind the Gap Between Sgd and Adam on Transformers, But Sign Descent Might Be. | Frederik Kunstner, Jacques Chen, Jonathan Wilder Lavington, Mark Schmidt |
| 2023 | ICML | Target-based Surrogates for Stochastic Optimization. | Jonathan Wilder Lavington, Sharan Vaswani, Reza Babanezhad Harikandeh, Mark Schmidt, Nicolas Le Roux |
| 2023 | ICML | Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning. | Wu Lin, Valentin Duruisseaux, Melvin Leok, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt |
| 2023 | UAI | Optimistic Thompson Sampling-based algorithms for episodic reinforcement learning. | Bingshan Hu, Tianyue H. Zhang, Nidhi Hegde, Mark Schmidt |
| 2022 | IJCAI | Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent (Extended Abstract). | Frederik Kunstner, Raunak Kumar, Mark Schmidt |
| 2021 | AISTATS | Homeomorphic-Invariance of EM: Non-Asymptotic Convergence in KL Divergence for Exponential Families via Mirror Descent. | Frederik Kunstner, Raunak Kumar, Mark Schmidt |
| 2021 | ICML | Tractable structured natural-gradient descent using local parameterizations. | Wu Lin, Frank Nielsen, Mohammad Emtiyaz Khan, Mark Schmidt |
| 2021 | ICML | Robust Asymmetric Learning in POMDPs. | Andrew Warrington, Jonathan Wilder Lavington, Adam Scibior, Mark Schmidt, Frank Wood |
| 2021 | WACV | AutoRetouch: Automatic Professional Face Retouching. | Alireza Shafaei, James J. Little, Mark Schmidt |
| 2020 | AISTATS | Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation. | Si Yi Meng, Sharan Vaswani, Issam Hadj Laradji, Mark Schmidt, Simon Lacoste-Julien |
| 2020 | ICIP | Proposal-Based Instance Segmentation With Point Supervision. | Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vzquez, Mark Schmidt |
| 2020 | ICML | Handling the Positive-Definite Constraint in the Bayesian Learning Rule. | Wu Lin, Mark Schmidt, Mohammad Emtiyaz Khan |
| 2020 | NOMS | xRAC: Execution and Access Control for Restricted Application Containers on Managed Hosts. | Frederik Hauser, Mark Schmidt, Michael Menth |
| 2019 | AISTATS | Distributed Maximization of "Submodular plus Diversity" Functions for Multi-label Feature Selection on Huge Datasets. | Mehrdad Ghadiri, Mark Schmidt |
| 2019 | AISTATS | Are we there yet? Manifold identification of gradient-related proximal methods. | Yifan Sun, Halyun Jeong, Julie Nutini, Mark Schmidt |
| 2019 | AISTATS | Fast and Faster Convergence of SGD for Over-Parameterized Models and an Accelerated Perceptron. | Sharan Vaswani, Francis R. Bach, Mark Schmidt |
| 2019 | BMVC | Where are the Masks: Instance Segmentation with Image-level Supervision. | Issam H. Laradji, David Vzquez, Mark Schmidt |
| 2019 | BMVC | A Less Biased Evaluation of Out-of-distribution Sample Detectors. | Alireza Shafaei, Mark Schmidt, James J. Little |
| 2019 | DNA | Efficient Parameter Estimation for DNA Kinetics Modeled as Continuous-Time Markov Chains. | Sedigheh Zolaktaf, Frits Dannenberg, Erik Winfree, Alexandre Bouchard-Ct, Mark Schmidt, Anne Condon |
| 2019 | ICML | Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations. | Wu Lin, Mohammad Emtiyaz Khan, Mark Schmidt |
| 2019 | IJCNN | Efficient Deep Gaussian Process Models for Variable-Sized Inputs. | Issam H. Laradji, Mark Schmidt, Vladimir Pavlovic, Minyoung Kim |
| 2018 | ECCV | Where Are the Blobs: Counting by Localization with Point Supervision. | Issam H. Laradji, Negar Rostamzadeh, Pedro O. Pinheiro, David Vzquez, Mark Schmidt |
| 2018 | ICLR | Online Learning Rate Adaptation with Hypergradient Descent. | Atilim Gunes Baydin, Robert Cornish, David Martnez-Rubio, Mark Schmidt, Frank Wood |
| 2017 | AISTATS | Horde of Bandits using Gaussian Markov Random Fields. | Sharan Vaswani, Mark Schmidt, Laks V. S. Lakshmanan |
| 2017 | CNSM | A software-defined firewall bypass for congestion offloading. | Florian Heimgaertner, Mark Schmidt, David Morgenstern, Michael Menth |
| 2017 | DNA | Inferring Parameters for an Elementary Step Model of DNA Structure Kinetics with Locally Context-Dependent Arrhenius Rates. | Sedigheh Zolaktaf, Frits Dannenberg, Xander Rudelis, Anne Condon, Joseph M. Schaeffer, Mark Schmidt, Chris Thachuk, Erik Winfree |
| 2017 | ICML | Model-Independent Online Learning for Influence Maximization. | Sharan Vaswani, Branislav Kveton, Zheng Wen, Mohammad Ghavamzadeh, Laks V. S. Lakshmanan, Mark Schmidt |
| 2016 | BMVC | Play and Learn: Using Video Games to Train Computer Vision Models. | Alireza Shafaei, James J. Little, Mark Schmidt |
| 2016 | UAI | Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions. | Mohammad Emtiyaz Khan, Reza Babanezhad, Wu Lin, Mark Schmidt, Masashi Sugiyama |
| 2016 | UAI | Convergence Rates for Greedy Kaczmarz Algorithms, and Randomized Kaczmarz Rules Using the Orthogonality Graph. | Julie Nutini, Behrooz Sepehry, Issam H. Laradji, Mark Schmidt, Hoyt A. Koepke, Alim Virani |
| 2015 | AISTATS | Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields. | Mark Schmidt, Reza Babanezhad, Mohamed Osama Ahmed, Aaron Defazio, Ann Clifton, Anoop Sarkar |
| 2015 | ICML | Coordinate Descent Converges Faster with the Gauss-Southwell Rule Than Random Selection. | Julie Nutini, Mark Schmidt, Issam H. Laradji, Michael P. Friedlander, Hoyt A. Koepke |
| 2014 | ISCC | Comparison of delay bounds for Ethernet networks based on simple Network Calculus algorithms. | Michael Menth, Mark Schmidt, Sebastian Veith, Stephan Kehrer, Andreas Dreher |
| 2014 | SIGCOMM | Demo: a virtualized lab testbed with physical network outlets for hands-on computer networking education. | Mark Schmidt, Florian Heimgaertner, Michael Menth |
| 2014 | SIGITE | A virtualized testbed with physical outlets for hands-on computer networking education. | Mark Schmidt, Florian Heimgaertner, Michael Menth |
| 2013 | ICML | Block-Coordinate Frank-Wolfe Optimization for Structural SVMs. | Simon Lacoste-Julien, Martin Jaggi, Mark Schmidt, Patrick Pletscher |
| 2011 | UAI | Generalized Fast Approximate Energy Minimization via Graph Cuts: a-Expansion b-Shrink Moves. | Mark Schmidt, Karteek Alahari |
| 2010 | MASS | Precise time of flight measurements in IEEE 802.11 networks by cross-correlating the sampled signal with a continuous Barker code. | Stefan Knig, Mark Schmidt, Christian Hoene |
| 2009 | CVPR | Increased discrimination in level set methods with embedded conditional random fields. | Dana Cobzas, Mark Schmidt |
| 2009 | UAI | Group Sparse Priors for Covariance Estimation. | Benjamin M. Marlin, Mark Schmidt, Kevin P. Murphy |
| 2009 | UAI | Modeling Discrete Interventional Data using Directed Cyclic Graphical Models. | Mark Schmidt, Kevin P. Murphy |
| 2008 | CVPR | Structure learning in random fields for heart motion abnormality detection. | Mark Schmidt, Kevin P. Murphy, Glenn Fung, Rmer Rosales |
| 2007 | AAAI | Learning Graphical Model Structure Using L1-Regularization Paths. | Mark Schmidt, Alexandru Niculescu-Mizil, Kevin P. Murphy |
| 2007 | ICCV | 3D Variational Brain Tumor Segmentation using a High Dimensional Feature Set. | Dana Cobzas, Neil Birkbeck, Mark Schmidt, Martin Jgersand, Albert Murtha |
| 2006 | AI | A Classification-Based Glioma Diffusion Model Using MRI Data. | Marianne Morris, Russell Greiner, Jrg Sander, Albert Murtha, Mark Schmidt |
| 2005 | ICMLA | Segmenting brain tumors using alignment-based features. | Mark Schmidt, Ilya Levner, Russell Greiner, Albert Murtha, Aalo Bistritz |