Michael C. Mozer

Publication Activity (10 Years)

Years Active: 1989-2024
Publications (10 Years): 56

Top Topics

Visual Representations

Similarity Metric

Intermediate Representations

Trained Classifiers

Top Venues

Publications

Matt Jones, Tyler R. Scott, Michael C. Mozer
Human-like Learning in Temporally Structured Environments. AAAI Spring Symposia (2024)
Yanlai Yang, Matt Jones, Michael C. Mozer, Mengye Ren
Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training. CoRR (2024)
Katherine L. Hermann, Hossein Mobahi, Thomas Fel, Michael C. Mozer
On the Foundations of Shortcut Learning. CoRR (2023)
Pratyush Maini, Michael C. Mozer, Hanie Sedghi, Zachary C. Lipton, J. Zico Kolter, Chiyuan Zhang
Can Neural Network Memorization Be Localized? CoRR (2023)
Ayush Chakravarthy, Trang Nguyen, Anirudh Goyal, Yoshua Bengio, Michael C. Mozer
Spotlight Attention: Robust Object-Centric Learning With a Spatial Locality Prior. CoRR (2023)
Gamaleldin F. Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C. Mozer, Thomas Kipf
SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos. CoRR (2022)
Amr Khalifa, Michael C. Mozer, Hanie Sedghi, Behnam Neyshabur, Ibrahim Alabdulmohsin
Layer-Stack Temperature Scaling. CoRR (2022)
Gamaleldin F. Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C. Mozer, Thomas Kipf
SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos. NeurIPS (2022)
Rebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer
Mitigating Bias in Calibration Error Estimation. AISTATS (2022)
Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. ICML (2022)
Shruthi Sukumar, Adrian F. Ward, Camden Elliott-Williams, Shabnam Hakimi, Michael C. Mozer
Overcoming Temptation: Incentive Design For Intertemporal Choice. CoRR (2022)
Utku Evci, Vincent Dumoulin, Hugo Larochelle, Michael C. Mozer
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning. CoRR (2022)
Tyler R. Scott, Ting Liu, Michael C. Mozer, Andrew C. Gallagher
An Empirical Study on Clustering Pretrained Embeddings: Is Deep Strictly Better? CoRR (2022)
Michael L. Iuzzolino, Michael C. Mozer, Samy Bengio
Training cascaded networks for speeded decisions using a temporal-difference loss. CoRR (2021)
Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael C. Mozer, Becca Roelofs
Soft Calibration Objectives for Neural Networks. CoRR (2021)
Brett D. Roads, Michael C. Mozer
Predicting the Ease of Human Category Learning Using Radial Basis Function Networks. Neural Comput. 33 (2) (2021)
Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer
Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers. ICML (2021)
Tyler R. Scott, Andrew C. Gallagher, Michael C. Mozer
von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning. ICCV (2021)
Tyler R. Scott, Andrew C. Gallagher, Michael C. Mozer
von Mises-Fisher Loss: An Exploration of Embedding Geometries for Supervised Learning. CoRR (2021)
David Y. J. Kim, Tyler R. Scott, Debshila Basu Mallick, Michael C. Mozer
Using Semantics of Textbook Highlights to Predict Student Comprehension and Knowledge Retention. iTextbooks@AIED (2021)
Michael L. Iuzzolino, Michael C. Mozer, Samy Bengio
Improving Anytime Prediction with Parallel Cascaded Networks and a Temporal-Difference Loss. NeurIPS (2021)
Mengye Ren, Tyler R. Scott, Michael L. Iuzzolino, Michael C. Mozer, Richard S. Zemel
Online Unsupervised Learning of Visual Representations and Categories. CoRR (2021)
Dianbo Liu, Alex Lamb, Kenji Kawaguchi, Anirudh Goyal, Chen Sun, Michael C. Mozer, Yoshua Bengio
Discrete-Valued Neural Communication. NeurIPS (2021)
Piotr Teterwak, Chiyuan Zhang, Dilip Krishnan, Michael C. Mozer
Understanding invariance via feedforward inversion of discriminatively trained classifiers. CoRR (2021)
Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer
Characterizing Structural Regularities of Labeled Data in Overparameterized Models. ICML (2021)
Archit Karandikar, Nicholas Cain, Dustin Tran, Balaji Lakshminarayanan, Jonathon Shlens, Michael C. Mozer, Becca Roelofs
Soft Calibration Objectives for Neural Networks. NeurIPS (2021)
Nino Scherrer, Olexa Bilaniuk, Yashas Annadani, Anirudh Goyal, Patrick Schwab, Bernhard Schölkopf, Michael C. Mozer, Yoshua Bengio, Stefan Bauer, Nan Rosemary Ke
Learning Neural Causal Models with Active Interventions. CoRR (2021)
Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer, Richard S. Zemel
Wandering Within a World: Online Contextualized Few-Shot Learning. CoRR (2020)
Chiyuan Zhang, Samy Bengio, Moritz Hardt, Michael C. Mozer, Yoram Singer
Identity Crisis: Memorization and Generalization Under Extreme Overparameterization. ICLR (2020)
Nicole M. Beckage, Michael C. Mozer, Eliana Colunga
Quantifying the Role of Vocabulary Knowledge in Predicting Future Word Learning. IEEE Trans. Cogn. Dev. Syst. 12 (2) (2020)
Rebecca Roelofs, Nicholas Cain, Jonathon Shlens, Michael C. Mozer
Mitigating bias in calibration error estimation. CoRR (2020)
Zeqian Li, Michael C. Mozer, Jacob Whitehill
Compositional Embeddings for Multi-Label One-Shot Learning. CoRR (2020)
Guy Davidson, Michael C. Mozer
Sequential Mastery of Multiple Visual Tasks: Networks Naturally Learn to Learn and Forget to Forget. CVPR (2020)
Ziheng Jiang, Chiyuan Zhang, Kunal Talwar, Michael C. Mozer
Exploring the Memorization-Generalization Continuum in Deep Learning. CoRR (2020)
Maria Attarian, Brett D. Roads, Michael C. Mozer
Transforming Neural Network Visual Representations to Predict Human Judgments of Similarity. CoRR (2020)
Alex Lamb, Jonathan Binas, Anirudh Goyal, Sandeep Subramanian, Ioannis Mitliagkas, Denis Kazakov, Yoshua Bengio, Michael C. Mozer
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations. CoRR (2019)
Tyler R. Scott, Karl Ridgeway, Michael C. Mozer
Stochastic Prototype Embeddings. CoRR (2019)
Michael L. Iuzzolino, Yoram Singer, Michael C. Mozer
Convolutional Bipartite Attractor Networks. CoRR (2019)
Guy Davidson, Michael C. Mozer
Sequential mastery of multiple tasks: Networks naturally learn to learn. CoRR (2019)
Tyler R. Scott, Karl Ridgeway, Michael C. Mozer
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning. CoRR (2018)
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio
Sparse Attentive Backtracking: Temporal Credit Assignment Through Reminding. NeurIPS (2018)
Mohammad M. Khajah, Michael C. Mozer, Sean Kelly, Brent Milne
Boosting Engagement with Educational Software Using Near Wins. AIED (2) (2018)
Tyler R. Scott, Karl Ridgeway, Michael C. Mozer
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning. NeurIPS (2018)
Karl Ridgeway, Michael C. Mozer
Open-Ended Content-Style Recombination Via Leakage Filtering. CoRR (2018)
Karl Ridgeway, Michael C. Mozer
Learning Deep Disentangled Embeddings with the F-Statistic Loss. CoRR (2018)
Michael C. Mozer, Denis Kazakov, Robert V. Lindsey
State-Denoised Recurrent Neural Networks. CoRR (2018)
Nan Rosemary Ke, Anirudh Goyal, Olexa Bilaniuk, Jonathan Binas, Michael C. Mozer, Chris Pal, Yoshua Bengio
Sparse Attentive Backtracking: Temporal CreditAssignment Through Reminding. CoRR (2018)
Karl Ridgeway, Michael C. Mozer
Learning Deep Disentangled Embeddings With the F-Statistic Loss. NeurIPS (2018)
Michael C. Mozer, Denis Kazakov, Robert V. Lindsey
Discrete Event, Continuous Time RNNs. CoRR (2017)
Ronald T. Kneusel, Michael C. Mozer
Improving Human-Machine Cooperative Visual Search With Soft Highlighting. ACM Trans. Appl. Percept. 15 (1) (2017)
Brett D. Roads, Michael C. Mozer
Improving Human-Machine Cooperative Classification Via Cognitive Theories of Similarity. Cogn. Sci. 41 (5) (2017)
Jake Snell, Karl Ridgeway, Renjie Liao, Brett D. Roads, Michael C. Mozer, Richard S. Zemel
Learning to generate images with perceptual similarity metrics. ICIP (2017)
Karl Ridgeway, Michael C. Mozer, Anita R. Bowles
Forgetting of Foreign-Language Skills: A Corpus-Based Analysis of Online Tutoring Software. Cogn. Sci. 41 (4) (2017)
Ronald T. Kneusel, Michael C. Mozer
Improving Human-Machine Cooperative Visual Search With Soft Highlighting. CoRR (2016)
Mohammad Khajah, Brett D. Roads, Robert V. Lindsey, Yun-En Liu, Michael C. Mozer
Designing Engaging Games Using Bayesian Optimization. CHI (2016)
Mohammad Khajah, Robert V. Lindsey, Michael C. Mozer
How deep is knowledge tracing? CoRR (2016)
Karl Ridgeway, Jake Snell, Brett Roads, Richard S. Zemel, Michael C. Mozer
Learning to generate images with perceptual similarity metrics. CoRR (2015)
Mohammad Khajah, Robert V. Lindsey, Michael C. Mozer
Maximizing Students' Retention via Spaced Review: Practical Guidance From Computational Models of Memory. Top. Cogn. Sci. 6 (1) (2014)
Robert V. Lindsey, Mohammad Khajah, Michael C. Mozer
Automatic Discovery of Cognitive Skills to Improve the Prediction of Student Learning. NIPS (2014)
Anup Doshi, Cuong Tran, Matthew H. Wilder, Michael C. Mozer, Mohan M. Trivedi
Sequential Dependencies in Driving. Cogn. Sci. 36 (5) (2012)
Michael C. Mozer, Benjamin Link, Harold Pashler
An Unsupervised Decontamination Procedure For Improving The Reliability Of Human Judgments. NIPS (2011)
Dan Knights, Todd Mytkowicz, Peter F. Sweeney, Michael C. Mozer, Amer Diwan
Blind Optimization for Exploiting Hardware Features. CC (2009)
Dan Knights, Michael C. Mozer, Nicolas Nicolov
Detecting Topic Drift with Compound Topic Models. ICWSM (2009)
Matt Jones, Michael C. Mozer, Sachiko Kinoshita
Optimal Response Initiation: Why Recent Experience Matters. NIPS (2008)
Michael C. Mozer, Adrian Fan
Top-Down modulation of neural responses in visual perception: a computational exploration. Nat. Comput. 7 (1) (2008)
Jeremy Reynolds, Michael C. Mozer
Temporal Dynamics of Cognitive Control. NIPS (2008)
Michael C. Mozer, Harold Pashler, Hadjar Homaei
Optimal Predictions in Everyday Cognition: The Wisdom of Individuals or Crowds? Cogn. Sci. 32 (7) (2008)
Sander M. Bohté, Michael C. Mozer
Reducing the Variability of Neural Responses: A Computational Theory of Spike-Timing-Dependent Plasticity. Neural Comput. 19 (2) (2007)
Michael C. Mozer, Michael Jones, Michael Shettel
Context Effects in Category Learning: An Investigation of Four Probabilistic Models. NIPS (2006)
Michael C. Mozer
Rational Models of Cognitive Control. UC (2006)
Matthias Hauswirth, Amer Diwan, Peter F. Sweeney, Michael C. Mozer
Automating vertical profiling. OOPSLA (2005)
Sander M. Bohté, Michael C. Mozer
Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity. BNAIC (2005)
Michael D. Colagrosso, Michael C. Mozer
Theories of Access Consciousness. NIPS (2004)
Sander M. Bohté, Michael C. Mozer
Reducing Spike Train Variability: A Computational Theory Of Spike-Timing Dependent Plasticity. NIPS (2004)
Michael C. Mozer, Robert H. Dodier, Michael D. Colagrosso, Cesar Guerra-Salcedo, Richard H. Wolniewicz
Prodding the ROC Curve: Constrained Optimization of Classifier Performance. NIPS (2001)
Harold Pashler, Michael C. Mozer, Christine R. Harris
Mating Strategies in a Darwinian Microworld: Simulating the Consequences of Female Reproductive Refractoriness. Adapt. Behav. 9 (1) (2001)
Michael C. Mozer, Michael D. Colagrosso, David E. Huber
A Rational Analysis of Cognitive Control in a Speeded Discrimination Task. NIPS (2001)
Michael C. Mozer, Richard H. Wolniewicz, David B. Grimes, Eric Johnson, Howard Kaushansky
Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry. IEEE Trans. Neural Networks Learn. Syst. 11 (3) (2000)
Michael C. Mozer
An Intelligent Environment Must Be Adaptive. IEEE Intell. Syst. 14 (2) (1999)
Haym Hirsh, Michael H. Coen, Michael C. Mozer, Richard Hasha, James L. Flanagan
Room service, AI-style. IEEE Intell. Syst. 14 (2) (1999)
Yayoi Uno, Michael C. Mozer
Neural net Architectures in Modeling Compositional Syntax: Prediction and Perception of Continuity in Minimalist Works by Phillip Glass and Louis Andriessen. ICMC (1997)
Michael C. Mozer
Neural Network Music Composition by Prediction: Exploring the Benefits of Psychoacoustic Constraints and Multi-scale Processing. Connect. Sci. 6 (2-3) (1994)
Michael C. Mozer, Richard S. Zemel, Marlene Behrmann, Christopher K. I. Williams
Learning to Segment Images Using Dynamic Feature Binding. Neural Comput. 4 (5) (1992)
Michael C. Mozer, Jonathan Bachrach
Discovering the Structure of a Reactive Environment by Exploration. Neural Comput. 2 (4) (1990)
Michael C. Mozer
A Focused Backpropagation Algorithm for Temporal Pattern Recognition. Complex Syst. 3 (4) (1989)