Randall Balestriero

ORCID

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 108

Top Venues

Publications

Mark Ibrahim, David Klindt, Randall Balestriero
Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations? CoRR (2024)
Aarash Feizi, Randall Balestriero, Adriana Romero-Soriano, Reihaneh Rabbany
GPS-SSL: Guided Positive Sampling to Inject Prior Into Self-Supervised Learning. CoRR (2024)
Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun
𝕏-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. CoRR (2024)
Randall Balestriero, Yann LeCun
Fast and Exact Enumeration of Deep Networks Partitions Regions. CoRR (2024)
Omer Ronen, Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk, Bin Yu
ScaLES: Scalable Latent Exploration Score for Pre-Trained Generative Networks. CoRR (2024)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
Deep Networks Always Grok and Here is Why. CoRR (2024)
Polina Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson
Understanding the Detrimental Class-level Effects of Data Augmentation. CoRR (2024)
Randall Balestriero, Yann LeCun
Learning by Reconstruction Produces Uninformative Features For Perception. CoRR (2024)
Randall Balestriero, Romain Cosentino, Sarath Shekkizhar
Characterizing Large Language Model Geometry Solves Toxicity Detection and Generation. CoRR (2023)
Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun
An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization. CoRR (2023)
Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
The SSL Interplay: Augmentations, Inductive Bias, and Generalization. CoRR (2023)
Vivien Cabannes, Alberto Bietti, Randall Balestriero
On Minimal Variations for Unsupervised Representation Learning. ICASSP (2023)
Quentin Garrido, Randall Balestriero, Laurent Najman, Yann LeCun
RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank. ICML (2023)
Polina Kirichenko, Mark Ibrahim, Randall Balestriero, Diane Bouchacourt, Shanmukha Ramakrishna Vedantam, Hamed Firooz, Andrew Gordon Wilson
Understanding the detrimental class-level effects of data augmentation. NeurIPS (2023)
Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. ICLR (2023)
Wei-Yin Ko, Daniel D'souza, Karina Nguyen, Randall Balestriero, Sara Hooker
FAIR-Ensemble: When Fairness Naturally Emerges From Deep Ensembling. CoRR (2023)
Mido Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas
The hidden uniform cluster prior in self-supervised learning. ICLR (2023)
Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent
Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning. Trans. Mach. Learn. Res. 2023 (2023)
Ahmed Imtiaz Humayun, Randall Balestriero, Guha Balakrishnan, Richard G. Baraniuk
SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries. CoRR (2023)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
Training Dynamics of Deep Network Linear Regions. CoRR (2023)
Vivien Cabannes, Léon Bottou, Yann LeCun, Randall Balestriero
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. ICCV (2023)
Florian Bordes, Randall Balestriero, Pascal Vincent
Towards Democratizing Joint-Embedding Self-Supervised Learning. CoRR (2023)
Vivien Cabannes, Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Alberto Bietti
The SSL Interplay: Augmentations, Inductive Bias, and Generalization. ICML (2023)
Ravid Shwartz-Ziv, Randall Balestriero, Kenji Kawaguchi, Tim G. J. Rudner, Yann LeCun
An Information Theory Perspective on Variance-Invariance-Covariance Regularization. NeurIPS (2023)
Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum
A Cookbook of Self-Supervised Learning. CoRR (2023)
Florian Bordes, Samuel Lavoie, Randall Balestriero, Nicolas Ballas, Pascal Vincent
A surprisingly simple technique to control the pretraining bias for better transfer: Expand or Narrow your representation. CoRR (2023)
Randall Balestriero, Yann LeCun
Police: Provably Optimal Linear Constraint Enforcement For Deep Neural Networks. ICASSP (2023)
Randall Balestriero, Yann LeCun
Fast and Exact Enumeration of Deep Networks Partitions Regions. ICASSP (2023)
Ali Siahkoohi, Rudy Morel, Randall Balestriero, Erwan Allys, Grégory Sainton, Taichi Kawamura, Maarten V. de Hoop
Martian time-series unraveled: A multi-scale nested approach with factorial variational autoencoders. CoRR (2023)
Vivien Cabannes, Léon Bottou, Yann LeCun, Randall Balestriero
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need. CoRR (2023)
Ahmed Imtiaz Humayun, Randall Balestriero, Guha Balakrishnan, Richard G. Baraniuk
SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries. CVPR (2023)
Randall Balestriero
Unsupervised Learning on a DIET: Datum IndEx as Target Free of Self-Supervision, Reconstruction, Projector Head. CoRR (2023)
Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk
No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. ICASSP (2022)
Randall Balestriero, Léon Bottou, Yann LeCun
The Effects of Regularization and Data Augmentation are Class Dependent. CoRR (2022)
Randall Balestriero, Léon Bottou, Yann LeCun
The Effects of Regularization and Data Augmentation are Class Dependent. NeurIPS (2022)
Cj Barberan, Sina Alemmohammad, Naiming Liu, Randall Balestriero, Richard G. Baraniuk
NeuroView-RNN: It's About Time. FAccT (2022)
Bobak Toussi Kiani, Randall Balestriero, Yubei Chen, Seth Lloyd, Yann LeCun
Joint Embedding Self-Supervised Learning in the Kernel Regime. CoRR (2022)
Rudolf H. Riedi, Randall Balestriero, Richard G. Baraniuk
Singular Value Perturbation and Deep Network Optimization. CoRR (2022)
Florian Bordes, Randall Balestriero, Pascal Vincent
High Fidelity Visualization of What Your Self-Supervised Representation Knows About. Trans. Mach. Learn. Res. 2022 (2022)
Mahmoud Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas
The Hidden Uniform Cluster Prior in Self-Supervised Learning. CoRR (2022)
Vishwanath Saragadam, Randall Balestriero, Ashok Veeraraghavan, Richard G. Baraniuk
DeepTensor: Low-Rank Tensor Decomposition with Deep Network Priors. CoRR (2022)
Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd
projUNN: efficient method for training deep networks with unitary matrices. NeurIPS (2022)
Ahmed Imtiaz Humayun, Randall Balestriero, Anastasios Kyrillidis, Richard G. Baraniuk
No More Than 6ft Apart: Robust K-Means via Radius Upper Bounds. CoRR (2022)
Quentin Garrido, Randall Balestriero, Laurent Najman, Yann LeCun
RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank. CoRR (2022)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values. CoRR (2022)
Bobak Toussi Kiani, Randall Balestriero, Yann LeCun, Seth Lloyd
projUNN: efficient method for training deep networks with unitary matrices. CoRR (2022)
Ravid Shwartz-Ziv, Randall Balestriero, Yann LeCun
What Do We Maximize in Self-Supervised Learning? CoRR (2022)
Randall Balestriero, Ishan Misra, Yann LeCun
A Data-Augmentation Is Worth A Thousand Samples: Exact Quantification From Analytical Augmented Sample Moments. CoRR (2022)
Randall Balestriero, Richard G. Baraniuk
Batch Normalization Explained. CoRR (2022)
C. J. Barberan, Sina Alemohammad, Naiming Liu, Randall Balestriero, Richard G. Baraniuk
NeuroView-RNN: It's About Time. CoRR (2022)
Vivien Cabannes, Alberto Bietti, Randall Balestriero
On minimal variations for unsupervised representation learning. CoRR (2022)
Grégoire Mialon, Randall Balestriero, Yann LeCun
Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations. CoRR (2022)
Haoran You, Randall Balestriero, Zhihan Lu, Yutong Kou, Huihong Shi, Shunyao Zhang, Shang Wu, Yingyan Lin, Richard G. Baraniuk
Max-Affine Spline Insights Into Deep Network Pruning. Trans. Mach. Learn. Res. 2022 (2022)
Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent
Guillotine Regularization: Improving Deep Networks Generalization by Removing their Head. CoRR (2022)
Ángel Bueno Rodríguez, Randall Balestriero, Silvio De Angelis, M. Carmen Benítez, Luciano Zuccarello, Richard G. Baraniuk, Jesús M. Ibáñez, Maarten V. de Hoop
Recurrent Scattering Network Detects Metastable Behavior in Polyphonic Seismo-Volcanic Signals for Volcano Eruption Forecasting. IEEE Trans. Geosci. Remote. Sens. 60 (2022)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining. ICLR (2022)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values. CVPR (2022)
Randall Balestriero, Ishan Misra, Yann LeCun
A Data-Augmentation Is Worth A Thousand Samples: Analytical Moments And Sampling-Free Training. NeurIPS (2022)
Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
Spatial Transformer K-Means. CoRR (2022)
Randall Balestriero, Yann LeCun
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods. NeurIPS (2022)
Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
Spatial Transformer K-Means. IEEECONF (2022)
Randall Balestriero, Yann LeCun
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods. CoRR (2022)
Randall Balestriero, Yann LeCun
POLICE: Provably Optimal Linear Constraint Enforcement for Deep Neural Networks. CoRR (2022)
Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov, Caner Hazirbas, Nicolas Ballas, Pascal Vincent, Michal Drozdzal, David Lopez-Paz, Mark Ibrahim
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations. CoRR (2022)
Randall Balestriero, Zichao Wang, Richard G. Baraniuk
DeepHull: Fast Convex Hull Approximation in High Dimensions. ICASSP (2022)
C. J. Barberan, Randall Balestriero, Richard G. Baraniuk
NeuroView: Explainable Deep Network Decision Making. CoRR (2021)
Ahmed Imtiaz Humayun, Randall Balestriero, Richard G. Baraniuk
MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retraining. CoRR (2021)
Randall Balestriero, Richard G. Baraniuk
Mad Max: Affine Spline Insights Into Deep Learning. Proc. IEEE 109 (5) (2021)
Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, Richard G. Baraniuk
Wearing A Mask: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels. ICASSP (2021)
Florian Bordes, Randall Balestriero, Pascal Vincent
High Fidelity Visualization of What Your Self-Supervised Representation Knows About. CoRR (2021)
Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang
Deep Autoencoders: From Understanding to Generalization Guarantees. MSML (2021)
Randall Balestriero, Hervé Glotin, Richard G. Baraniuk
Interpretable and Learnable Super-Resolution Time-Frequency Representation. MSML (2021)
Randall Balestriero, Haoran You, Zhihan Lu, Yutong Kou, Yingyan Lin, Richard G. Baraniuk
Max-Affine Spline Insights Into Deep Network Pruning. CoRR (2021)
Randall Balestriero, Richard G. Baraniuk
Fast Jacobian-Vector Product for Deep Networks. CoRR (2021)
Sina Alemohammad, Zichao Wang, Randall Balestriero, Richard G. Baraniuk
The Recurrent Neural Tangent Kernel. ICLR (2021)
Randall Balestriero, Jerome Pesenti, Yann LeCun
Learning in High Dimension Always Amounts to Extrapolation. CoRR (2021)
Sina Alemohammad, Hossein Babaei, Randall Balestriero, Matt Y. Cheung, Ahmed Imtiaz Humayun, Daniel LeJeune, Naiming Liu, Lorenzo Luzi, Jasper Tan, Zichao Wang, Richard G. Baraniuk
Wearing a MASK: Compressed Representations of Variable-Length Sequences Using Recurrent Neural Tangent Kernels. CoRR (2020)
Romain Cosentino, Randall Balestriero
Sparse Multi-Family Deep Scattering Network. CoRR (2020)
Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang
Universal Frame Thresholding. IEEE Signal Process. Lett. 27 (2020)
Randall Balestriero
SymJAX: symbolic CPU/GPU/TPU programming. CoRR (2020)
Randall Balestriero, Sebastien Paris, Richard G. Baraniuk
Max-Affine Spline Insights into Deep Generative Networks. CoRR (2020)
Romain Cosentino, Randall Balestriero, Richard G. Baraniuk, Behnaam Aazhang
Provable Finite Data Generalization with Group Autoencoder. CoRR (2020)
Lorenzo Luzi, Randall Balestriero, Richard G. Baraniuk
Ensembles of Generative Adversarial Networks for Disconnected Data. CoRR (2020)
Randall Balestriero, Hervé Glotin, Richard G. Baraniuk
Interpretable Super-Resolution via a Learned Time-Series Representation. CoRR (2020)
Sina Alemohammad, Randall Balestriero, Zichao Wang, Richard G. Baraniuk
Scalable Neural Tangent Kernel of Recurrent Architectures. CoRR (2020)
Randall Balestriero, Sebastien Paris, Richard G. Baraniuk
Analytical Probability Distributions and EM-Learning for Deep Generative Networks. CoRR (2020)
Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan M. Sengupta, Richard G. Baraniuk, Behnaam Aazhang
Interpretable Image Clustering via Diffeomorphism-Aware K-Means. CoRR (2020)
Sina Alemohammad, Zichao Wang, Randall Balestriero, Richard G. Baraniuk
The Recurrent Neural Tangent Kernel. CoRR (2020)
Randall Balestriero, Sebastien Paris, Richard G. Baraniuk
Analytical Probability Distributions and Exact Expectation-Maximization for Deep Generative Networks. NeurIPS (2020)
Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard G. Baraniuk
The Geometry of Deep Networks: Power Diagram Subdivision. NeurIPS (2019)
Zichao Wang, Randall Balestriero, Richard G. Baraniuk
A Max-Affine Spline Perspective of Recurrent Neural Networks. ICLR (Poster) (2019)
Randall Balestriero, Richard G. Baraniuk
From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference. ICLR (Poster) (2019)
Randall Balestriero, Romain Cosentino, Behnaam Aazhang, Richard G. Baraniuk
The Geometry of Deep Networks: Power Diagram Subdivision. CoRR (2019)
Hamid Javadi, Randall Balestriero, Richard G. Baraniuk
A Hessian Based Complexity Measure for Deep Networks. CoRR (2019)
Randall Balestriero, Hervé Glotin, Richard G. Baraniuk
Semi-Supervised Learning Enabled by Multiscale Deep Neural Network Inversion. CoRR (2018)
Randall Balestriero, Richard G. Baraniuk
A Spline Theory of Deep Networks. ICML (2018)
Randall Balestriero, Romain Cosentino, Hervé Glotin, Richard G. Baraniuk
Spline Filters For End-to-End Deep Learning. ICML (2018)
Randall Balestriero, Richard G. Baraniuk
From Hard to Soft: Understanding Deep Network Nonlinearities via Vector Quantization and Statistical Inference. CoRR (2018)
Randall Balestriero, Richard G. Baraniuk
A Spline Theory of Deep Networks (Extended Version). CoRR (2018)
Randall Balestriero, Vincent Roger, Hervé Glotin, Richard G. Baraniuk
Semi-Supervised Learning via New Deep Network Inversion. CoRR (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Randall Balestriero