ML Anthology

Mozer, Michael

56 publications

NeurIPS 2024 Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, Siyuan Guo, Michal Valko, Timothy Lillicrap, Danilo Rezende, Yoshua Bengio, Michael Mozer, Sanjeev Arora
AAAI 2023 Adaptive Discrete Communication Bottlenecks with Dynamic Vector Quantization for Heterogeneous Representational Coarseness Dianbo Liu, Alex Lamb, Xu Ji, Pascal Tikeng Notsawo Jr., Michael Mozer, Yoshua Bengio, Kenji Kawaguchi
NeurIPS 2022 SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos Gamaleldin Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael Mozer, Thomas Kipf
AISTATS 2021 Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information Across Layers Alex Lamb, Anirudh Goyal, Agnieszka Słowik, Michael Mozer, Philippe Beaudoin, Yoshua Bengio
WACV 2021 Compositional Embeddings for Multi-Label One-Shot Learning Zeqian Li, Michael Mozer, Jacob Whitehill
NeurIPS 2021 Discrete-Valued Neural Communication Dianbo Liu, Alex M Lamb, Kenji Kawaguchi, Anirudh Goyal ALIAS PARTH Goyal, Chen Sun, Michael Mozer, Yoshua Bengio
NeurIPS 2021 Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss Michael Iuzzolino, Michael Mozer, Samy Bengio
NeurIPS 2021 Neural Production Systems Anirudh Goyal ALIAS PARTH Goyal, Aniket Didolkar, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, Yoshua Bengio
NeurIPS 2021 Soft Calibration Objectives for Neural Networks Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael Mozer, Becca Roelofs
ICML 2020 Learning to Combine Top-Down and Bottom-up Signals in Recurrent Neural Networks with Attention over Modules Sarthak Mittal, Alex Lamb, Anirudh Goyal, Vikram Voleti, Murray Shanahan, Guillaume Lajoie, Michael Mozer, Yoshua Bengio
ICML 2019 State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Yoshua Bengio, Michael Mozer
NeurIPS 2018 Adapted Deep Embeddings: A Synthesis of Methods for K-Shot Inductive Transfer Learning Tyler Scott, Karl Ridgeway, Michael Mozer
NeurIPS 2018 Learning Deep Disentangled Embeddings with the F-Statistic Loss Karl Ridgeway, Michael Mozer
NeurIPS 2018 Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding Nan Rosemary Ke, Anirudh Goyal ALIAS PARTH Goyal, Olexa Bilaniuk, Jonathan Binas, Michael Mozer, Chris Pal, Yoshua Bengio
NeurIPS 2014 Automatic Discovery of Cognitive Skills to Improve the Prediction of Student Learning Robert Lindsey, Mohammad Khajah, Michael Mozer
NeurIPS 2013 Optimizing Instructional Policies Robert Lindsey, Michael Mozer, William J Huggins, Harold Pashler
NeurIPS 2011 An Unsupervised Decontamination Procedure for Improving the Reliability of Human Judgments Michael Mozer, Benjamin Link, Harold Pashler
NeurIPS 2010 Improving Human Judgments by Decontaminating Sequential Dependencies Michael Mozer, Harold Pashler, Matthew Wilder, Robert Lindsey, Matt Jones, Michael N. Jones
NeurIPS 2009 Predicting the Optimal Spacing of Study: A Multiscale Context Model of Memory Harold Pashler, Nicholas Cepeda, Robert Lindsey, Ed Vul, Michael Mozer
NeurIPS 2009 Sequential Effects Reflect Parallel Learning of Multiple Environmental Regularities Matthew Wilder, Matt Jones, Michael Mozer
NeurIPS 2008 Optimal Response Initiation: Why Recent Experience Matters Matt Jones, Sachiko Kinoshita, Michael Mozer
NeurIPS 2008 Temporal Dynamics of Cognitive Control Jeremy Reynolds, Michael Mozer
NeurIPS 2007 Experience-Guided Search: A Theory of Attentional Control David Baldwin, Michael Mozer
NeurIPS 2006 Context Effects in Category Learning: An Investigation of Four Probabilistic Models Michael Mozer, Michael Shettel, Michael P. Holmes
NeurIPS 2005 Top-Down Control of Visual Attention: A Rational Account Michael Shettel, Shaun Vecera, Michael Mozer
NeurIPS 2004 Reducing Spike Train Variability: A Computational Theory of Spike-Timing Dependent Plasticity Sander M. Bohte, Michael Mozer
NeurIPS 2004 Theories of Access Consciousness Michael D. Colagrosso, Michael Mozer
ICML 2003 Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic Lian Yan, Robert H. Dodier, Michael Mozer, Richard H. Wolniewicz
NeurIPS 2002 Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems Sepp Hochreiter, Michael Mozer, Klaus Obermayer
NeurIPS 2001 A Rational Analysis of Cognitive Control in a Speeded Discrimination Task Michael Mozer, Michael D. Colagrosso, David E. Huber
NeCo 2001 Localist Attractor Networks Richard S. Zemel, Michael Mozer
NeurIPS 2001 Prodding the ROC Curve: Constrained Optimization of Classifier Performance Michael Mozer, Robert Dodier, Michael D. Colagrosso, Cesar Guerra-Salcedo, Richard Wolniewicz
NeurIPS 2000 Beyond Maximum Likelihood and Density Estimation: A Sample-Based Criterion for Unsupervised Learning of Complex Models Sepp Hochreiter, Michael Mozer
NeurIPS 2000 The Interplay of Symbolic and Subsymbolic Processes in Anagram Problem Solving David B. Grimes, Michael Mozer
NeurIPS 1999 A Generative Model for Attractor Dynamics Richard S. Zemel, Michael Mozer
NeurIPS 1999 Churn Reduction in the Wireless Industry Michael Mozer, Richard H. Wolniewicz, David B. Grimes, Eric Johnson, Howard Kaushansky
NeurIPS 1999 Robust Recognition of Noisy and Superimposed Patterns via Selective Attention Soo-Young Lee, Michael Mozer
NeurIPS 1998 A Principle for Unsupervised Hierarchical Decomposition of Visual Scenes Michael Mozer
NeurIPS 1997 A Superadditive-Impairment Theory of Optic Aphasia Michael Mozer, Mark Sitton, Martha J. Farah
NeurIPS 1996 The Neurothermostat: Predictive Optimal Control of Residential Heating Systems Michael Mozer, Lucky Vidmar, Robert H. Dodier
NeurIPS 1994 On the Computational Utility of Consciousness Donald W. Mathis, Michael Mozer
NeurIPS 1994 Template-Based Algorithms for Connectionist Rule Extraction Jay A. Alexander, Michael Mozer
NeurIPS 1993 A Unified Gradient-Descent/Clustering Architecture for Finite State Machine Induction Sreerupa Das, Michael Mozer
IJCAI 1993 Dynamic Conflict Resolution in a Connectionist Rule-Based System Clayton McMillan, Michael Mozer, Paul Smolensky
NeurIPS 1992 A Connectionist Symbol Manipulator That Discovers the Structure of Context-Free Languages Michael Mozer, Sreerupa Das
NeurIPS 1992 Directional-Unit Boltzmann Machines Richard S. Zemel, Christopher K. I. Williams, Michael Mozer
NeurIPS 1992 Metamorphosis Networks: An Alternative to Constructive Models Brian V. Bonnlander, Michael Mozer
NeurIPS 1991 Induction of Multiscale Temporal Structure Michael Mozer
NeurIPS 1991 Learning to Segment Images Using Dynamic Feature Binding Michael Mozer, Richard S. Zemel, Marlene Behrmann
NeurIPS 1991 Rule Induction Through Integrated Symbolic and Subsymbolic Processing Clayton McMillan, Michael Mozer, Paul Smolensky
MLJ 1991 SLUG: A Connectionist Architecture for Inferring the Structure of Finite-State Environments Michael Mozer, Jonathan Bachrach
NeurIPS 1990 Connectionist Music Composition Based on Melodic and Stylistic Constraints Michael Mozer, Todd Soukup
NeurIPS 1990 Discovering Discrete Distributed Representations with Iterative Competitive Learning Michael Mozer
NeurIPS 1989 Discovering the Structure of a Reactive Environment by Exploration Michael Mozer, Jonathan Bachrach
NeurIPS 1989 TRAFFIC: Recognizing Objects Using Hierarchical Reference Frame Transformations Richard S. Zemel, Michael Mozer, Geoffrey E. Hinton
NeurIPS 1988 Skeletonization: A Technique for Trimming the Fat from a Network via Relevance Assessment Michael Mozer, Paul Smolensky