Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions

5 May 2017

Papers citing "Analysis and Design of Convolutional Networks via Hierarchical Tensor Decompositions"

27 / 27 papers shown

Title
Reduced Order Models and Conditional Expectation -- Analysing Parametric Low-Order Approximations Hermann G. Matthies 42 0 0 17 Feb 2025
Lecture Notes on Linear Neural Networks: A Tale of Optimization and Generalization in Deep Learning Nadav Cohen Noam Razin 35 0 0 25 Aug 2024
Incrementally-Computable Neural Networks: Efficient Inference for Dynamic Inputs Or Sharir Anima Anandkumar 32 0 0 27 Jul 2023
What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement Yotam Alexander Nimrod De La Vega Noam Razin Nadav Cohen 26 4 0 20 Mar 2023
On the Ability of Graph Neural Networks to Model Interactions Between Vertices Noam Razin Tom Verbin Nadav Cohen 23 10 0 29 Nov 2022
Transformer Vs. MLP-Mixer: Exponential Expressive Gap For NLP Problems D. Navon A. Bronstein MoE 38 0 0 17 Aug 2022
STD-NET: Search of Image Steganalytic Deep-learning Architecture via Hierarchical Tensor Decomposition Shunquan Tan Qiushi Li Laiyuan Li Bin Li Jiwu Huang 19 4 0 12 Jun 2022
Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks Noam Razin Asaf Maman Nadav Cohen 46 29 0 27 Jan 2022
The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design Yoav Levine Noam Wies Daniel Jannai D. Navon Yedid Hoshen Amnon Shashua AI4CE 35 36 0 09 Oct 2021
Learning a Self-Expressive Network for Subspace Clustering Shangzhi Zhang Chong You René Vidal Chun-Guang Li 29 44 0 08 Oct 2021
Which transformer architecture fits my data? A vocabulary bottleneck in self-attention Noam Wies Yoav Levine Daniel Jannai Amnon Shashua 40 20 0 09 May 2021
Towards Extremely Compact RNNs for Video Recognition with Fully Decomposed Hierarchical Tucker Structure Miao Yin Siyu Liao Xiao-Yang Liu Xiaodong Wang Bo Yuan AI4TS 19 31 0 12 Apr 2021
Implicit Regularization in Tensor Factorization Noam Razin Asaf Maman Nadav Cohen 30 48 0 19 Feb 2021
Computational Separation Between Convolutional and Fully-Connected Networks Eran Malach Shai Shalev-Shwartz 19 26 0 03 Oct 2020
Complexity for deep neural networks and other characteristics of deep feature representations R. Janik Przemek Witaszczyk 7 5 0 08 Jun 2020
Implicit Regularization in Deep Learning May Not Be Explainable by Norms Noam Razin Nadav Cohen 24 155 0 13 May 2020
Compressing Recurrent Neural Networks Using Hierarchical Tucker Tensor Decomposition Miao Yin Siyu Liao Xiao-Yang Liu Xiaodong Wang Bo Yuan 40 24 0 09 May 2020
Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning I. Glasser R. Sweke Nicola Pancotti Jens Eisert J. I. Cirac 20 123 0 08 Jul 2019
Number-State Preserving Tensor Networks as Classifiers for Supervised Learning G. Evenbly 17 11 0 15 May 2019
Shortcut Matrix Product States and its applications Zhuan Li Pan Zhang 11 9 0 13 Dec 2018
Deep Compression of Sum-Product Networks on Tensor Networks Ching-Yun Ko Cong Chen Yuke Zhang Kim Batselier Ngai Wong TPM 20 2 0 09 Nov 2018
From probabilistic graphical models to generalized tensor networks for supervised learning I. Glasser Nicola Pancotti J. I. Cirac AI4CE 69 74 0 15 Jun 2018
Interpreting Deep Learning: The Machine Learning Rorschach Test? Adam S. Charles AAML HAI AI4CE 19 9 0 01 Jun 2018
Universal approximations of invariant maps by neural networks Dmitry Yarotsky 32 205 0 26 Apr 2018
On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization Sanjeev Arora Nadav Cohen Elad Hazan 11 456 0 19 Feb 2018
Information Scaling Law of Deep Neural Networks Xiao-Yang Liu 28 0 0 13 Feb 2018
Provably efficient neural network representation for image classification Yichen Huang 19 4 0 13 Nov 2017