On the Expressive Power of Deep Learning: A Tensor Analysis

16 September 2015

Papers citing "On the Expressive Power of Deep Learning: A Tensor Analysis"

50 / 246 papers shown

Title
Verification of ML Systems via Reparameterization Jean-Baptiste Tristan Joseph Tassarotti Koundinya Vajjha Michael L. Wick A. Banerjee AAML 25 6 0 14 Jul 2020
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 16 51 0 09 Jul 2020
CacheNet: A Model Caching Framework for Deep Learning Inference on the Edge Yihao Fang Shervin Manzuri Shalmani Rong Zheng 9 7 0 03 Jul 2020
Learning with tree tensor networks: complexity estimates and model selection Bertrand Michel A. Nouy 8 14 0 02 Jul 2020
Approximation Theory of Tree Tensor Networks: Tensorized Univariate Functions -- Part I Mazen Ali A. Nouy 8 12 0 30 Jun 2020
Hybrid Tensor Decomposition in Neural Network Compression Bijiao Wu Dingheng Wang Guangshe Zhao Lei Deng Guoqi Li 33 46 0 29 Jun 2020
The Depth-to-Width Interplay in Self-Attention Yoav Levine Noam Wies Or Sharir Hofit Bata Amnon Shashua 30 45 0 22 Jun 2020
Deep Polynomial Neural Networks Grigorios G. Chrysos Stylianos Moschoglou Giorgos Bouritsas Jiankang Deng Yannis Panagakis S. Zafeiriou 29 92 0 20 Jun 2020
Measuring Model Complexity of Neural Networks with Curve Activation Functions X. Hu Weiqing Liu Jiang Bian J. Pei 16 20 0 16 Jun 2020
Seq2Tens: An Efficient Representation of Sequences by Low-Rank Tensor Projections Csaba Tóth Patric Bonnier Harald Oberhauser AI4TS 11 12 0 12 Jun 2020
Complexity for deep neural networks and other characteristics of deep feature representations R. Janik Przemek Witaszczyk 12 5 0 08 Jun 2020
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth Guy Bresler Dheeraj M. Nagaraj 11 21 0 07 Jun 2020
Transferring Inductive Biases through Knowledge Distillation Samira Abnar Mostafa Dehghani Willem H. Zuidema 33 57 0 31 May 2020
Deep convolutional tensor network Philip Blagoveschensky Anh-Huy Phan 15 4 0 29 May 2020
Physically interpretable machine learning algorithm on multidimensional non-linear fields Rem-Sophia Mouradi C. Goeury O. Thual F. Zaoui P. Tassi OOD 6 7 0 28 May 2020
PDE constraints on smooth hierarchical functions computed by neural networks Khashayar Filom Konrad Paul Kording Roozbeh Farhoodi 21 0 0 18 May 2020
Implicit Regularization in Deep Learning May Not Be Explainable by Norms Noam Razin Nadav Cohen 24 155 0 13 May 2020
Depth Enables Long-Term Memory for Recurrent Neural Networks A. Ziv 18 30 0 23 Mar 2020
Tensor Networks for Probabilistic Sequence Modeling Jacob Miller Guillaume Rabusseau John Terilla 11 5 0 02 Mar 2020
Tensor network approaches for learning non-linear dynamical laws Alex Goessmann M. Götte I. Roth R. Sweke Gitta Kutyniok Jens Eisert AI4CE 6 17 0 27 Feb 2020
$Learning the mapping $\mathbf{x}\mapsto \sum_{i=1}^d x_i^2$: the cost of finding the needle in a haystack$ Learning the mapping $\mathbf{x}\mapsto \sum_{i=1}^d x_i^2$ : the cost of finding the needle in a haystack Jiefu Zhang Leonardo Zepeda-Núnez Yuan Yao Lin Lin 8 0 0 24 Feb 2020
Quasi-Equivalence of Width and Depth of Neural Networks Fenglei Fan Rongjie Lai Ge Wang 22 11 0 06 Feb 2020
Supervised Learning for Non-Sequential Data: A Canonical Polyadic Decomposition Approach A. Haliassos Kriton Konstantinidis Danilo P. Mandic 29 1 0 27 Jan 2020
Efficient Black-box Assessment of Autonomous Vehicle Safety J. Norden Matthew O'Kelly Aman Sinha 27 66 0 08 Dec 2019
Compositional Hierarchical Tensor Factorization: Representing Hierarchical Intrinsic and Extrinsic Causal Factors M. Alex O. Vasilescu E. Kim CoGe CVBM 23 12 0 11 Nov 2019
A Formal Proof of PAC Learnability for Decision Stumps Joseph Tassarotti Koundinya Vajjha Anindya Banerjee Jean-Baptiste Tristan 19 2 0 01 Nov 2019
Learning Without Loss V. Elser 9 11 0 29 Oct 2019
4-Connected Shift Residual Networks Andrew Brown Pascal Mettes M. Worring 3DPC 28 8 0 22 Oct 2019
Tensor-based algorithms for image classification Stefan Klus Patrick Gelß 16 31 0 04 Oct 2019
Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network Taiji Suzuki Hiroshi Abe Tomoaki Nishimura AI4CE 25 43 0 25 Sep 2019
Optimal Function Approximation with Relu Neural Networks Bo Liu Yi Liang 25 33 0 09 Sep 2019
Fast generalization error bound of deep learning without scale invariance of activation functions Y. Terada Ryoma Hirose MLT 13 6 0 25 Jul 2019
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 28 123 0 08 Jul 2019
Error bounds for deep ReLU networks using the Kolmogorov--Arnold superposition theorem Hadrien Montanelli Haizhao Yang 6 90 0 27 Jun 2019
A Review on Deep Learning in Medical Image Reconstruction Hai-Miao Zhang Bin Dong MedIm 35 122 0 23 Jun 2019
Factorized Higher-Order CNNs with an Application to Spatio-Temporal Emotion Estimation Jean Kossaifi Antoine Toisoul Adrian Bulat Yannis Panagakis Timothy M. Hospedales M. Pantic CVBM 15 80 0 14 Jun 2019
Deep Semi-Supervised Anomaly Detection Lukas Ruff Robert A. Vandermeulen Nico Görnitz Alexander Binder Emmanuel Müller K. Müller Marius Kloft UQCV 9 540 0 06 Jun 2019
Deep ReLU Networks Have Surprisingly Few Activation Patterns Boris Hanin David Rolnick 16 220 0 03 Jun 2019
Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade T. Lindeberg 27 19 0 29 May 2019
On the Expressive Power of Deep Polynomial Neural Networks Joe Kileel Matthew Trager Joan Bruna 27 82 0 29 May 2019
Expression of Fractals Through Neural Network Functions Nadav Dym B. Sober Ingrid Daubechies 13 14 0 27 May 2019
Tucker Decomposition Network: Expressive Power and Comparison Ye Liu Junjun Pan Michael K. Ng 24 1 0 23 May 2019
Detection of Review Abuse via Semi-Supervised Binary Multi-Target Tensor Decomposition Anil R. Yelundur Vineet Chaoji Bamdev Mishra 9 7 0 15 May 2019
Approximation spaces of deep neural networks Rémi Gribonval Gitta Kutyniok M. Nielsen Felix Voigtländer 13 124 0 03 May 2019
Depth Separations in Neural Networks: What is Actually Being Separated? Itay Safran Ronen Eldan Ohad Shamir MDE 21 36 0 15 Apr 2019
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs Gitta Kutyniok P. Petersen Mones Raslan R. Schneider 23 197 0 31 Mar 2019
Is Deeper Better only when Shallow is Good? Eran Malach Shai Shalev-Shwartz 28 45 0 08 Mar 2019
Implicit Regularization in Over-parameterized Neural Networks M. Kubo Ryotaro Banno Hidetaka Manabe Masataka Minoji 19 23 0 05 Mar 2019
Universal approximations of permutation invariant/equivariant functions by deep neural networks Akiyoshi Sannai Yuuki Takai Matthieu Cordonnier 29 67 0 05 Mar 2019
$Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms$ Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms Ingo Gühring Gitta Kutyniok P. Petersen 25 199 0 21 Feb 2019