Deep Fried Convnets

Yang, Zichao, Moczulski, Marcin, Denil, Misha, De Freitas, Nando, Song, Le, Wang, Ziyu·2015·2015 IEEE International Conference on Computer Vision (ICCV)
DOI 10.1109/iccv.2015.173

Cited by (215)

Items 101–200 of 215

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  2. UnCNN: A New Directed CNN Model for Isolated Arabic Handwritten Characters Recognition
    Mohsine El Khayati, Youssfi Elkettani · 2022 · Arabian Journal for Science and Engineering
  3. Deep SimNets
    Nadav Cohen, Or Sharir, Amnon Shashua · 2016 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  4. A Multilayer Network-Based Approach to Represent, Explore and Handle Convolutional Neural Networks
    Alessia Amelio, Gianluca Bonifazi, Enrico Corradini, Domenico Ursino A, Luca Virgili · 2022 · Cognitive Computation
  5. High Resolution Feature Recovering for Accelerating Urban Scene Parsing
    Rui Zhang, Sheng Tang, Luoqi Liu, Yongdong Zhang, Jintao Li, Shuicheng Yan · 2018 · International Joint Conference on Artificial Intelligence
  6. Hierarchical Discriminative Deep Dictionary Learning
    Ulises Rodríguez‐Domínguez, Oscar Dalmau · 2020 · IEEE Access
  7. A 25.1-TOPS/W Sparsity-Aware Hybrid CNN-GCN Deep Learning SoC for Mobile Augmented Reality
    Wen-Cong Huang, I-Ting Lin, Ying‐Sheng Lin, Wen-Ching Chen, Liang-Yi Lin, Nian-Shyang Chang, Chun‐Pin Lin, Chi‐Shi Chen, Chia‐Hsiang Yang · 2024 · IEEE Journal of Solid-State Circuits
  8. Tensorized Projection for High-Dimensional Binary Embedding
    Weixiang Hong, Jingjing Meng, Junsong Yuan · 2018 · Proceedings of the AAAI Conference on Artificial Intelligence
  9. Improving the Capacity of Very Deep Networks with Maxout Units
    Oyebade Kayode Oyedotun, Abd El Rahman Shabayek, Djamila Aouada, Björn Ottersten · 2018 · IEEE International Conference on Acoustics Speech and Signal Processing
  10. Hybrid Binary Networks: Optimizing for Accuracy, Efficiency and Memory
    Ameya Prabhu, Vishal Batchu, Rohit Gajawada, Sri Aurobindo Munagala, Anoop Namboodiri · 2018 · IEEE Winter Conference on Applications of Computer Vision
  11. Fuzzy qualitative deep compression network
    Wei Ren Tan, Chee Seng Chan, Hernan E. Aguirre, Kiyoshi Tanaka · 2017 · Neurocomputing
  12. Knowledge Squeezed Adversarial Network Compression
    Changyong Shu, Peng Li, Yuan Xie, Yanyun Qu, Longquan Dai, Lizhuang Ma · 2019 · arXiv (Cornell University)
  13. Neural Network Compression via Learnable Wavelet Transforms
    Moritz Wolter, Shaohui Lin, Angela Yao · 2020 · Lecture notes in computer science
  14. Real-Valued Embeddings and Sketches for Fast Distance and Similarity Estimation
    Dmitri A. Rachkovskij · 2016 · Cybernetics and Systems Analysis
  15. Deriving Compact Feature Representations Via Annealed Contraction
    Muhammad A. Shah, Bhiksha Raj · 2020 · IEEE International Conference on Acoustics Speech and Signal Processing
  16. Compressing Deep Convolutional Neural Networks by Stacking Low-dimensional Binary Convolution Filters
    Weichao Lan, Liang Lan · 2021 · Proceedings of the AAAI Conference on Artificial Intelligence
  17. Quintuple-Media Joint Correlation Learning With Deep Compression and Regularization
    Yuxin Peng, Jinwei Qi · 2019 · IEEE Transactions on Circuits and Systems for Video Technology
  18. Reduced memory region based deep Convolutional Neural Network detection
    Denis Tomè, Bondi Luca, Luca Baroffio, Stefano Tubaro, Emanuele Plebani, Pau Danilo · 2016 · UCL Discovery (University College London)
  19. Resistive Crossbar-Aware Neural Network Design and Optimization
    Muhammad Abdullah Hanif, Aditya Manglik, Muhammad Shafique · 2020 · IEEE Access
  20. Continuous Kernel Learning
    John Moeller, Vivek Srikumar, Sarathkrishna Swaminathan, Suresh Venkatasubramanian, Dustin J. Webb · 2016 · Lecture notes in computer science
  21. Neural Cellular Automata Manifold
    Alejandro Hernandez Ruiz, Armand Vilalta, Francesc Moreno-Noguer · 2021 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
  22. Structured Matrices and Their Application in Neural Networks: A Survey
    Matthias Kissel, Klaus J. Diepold · 2023 · New Generation Computing
  23. Reduced memory region based deep Convolutional Neural Network detection
    Denis Tomè, Luca Bondi, Luca Baroffio, Stefano Tubaro, Emanuele Plebani, Danilo Pau · 2016 · IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin)
  24. Fried Binary Embedding: From High-Dimensional Visual Features to High-Dimensional Binary Codes
    Weixiang Hong, Junsong Yuan · 2018 · IEEE Transactions on Image Processing
  25. Training Compact Deep Learning Models for Video Classification Using Circulant Matrices
    Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif C · 2019 · Lecture notes in computer science
  26. Facial Soft Biometrics Detection on Low Power Devices
    Manolis Vasileiadis, Georgios Stavropoulos, Dimitrios K. Tzovaras · 2019 · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
  27. Deep Kernel-Based Optimal Control Prediction in Aerospace Missions
    Hongjue Li, Wen Yao, Yunfeng Dong, Qing Zhong Gao, Yue Cheng Deng · 2021 · IEEE Transactions on Aerospace and Electronic Systems
  28. When Sparse Neural Network Meets Label Noise Learning: A Multistage Learning Framework
    Runqing Jiang, Yan Yan, Jing‐Hao Xue, Biao Wang, Hanzi Wang · 2022 · IEEE Transactions on Neural Networks and Learning Systems
  29. Automatic Configuration of Deep Neural Networks with EGO
    Bas van Stein, Hao Wang, Thomas Bäck · 2018 · arXiv (Cornell University)
  30. LCNN: Lookup-based Convolutional Neural Network
    Hessam Bagherinezhad, Mohammad Rastegari, Ali Farhadi · 2016 · arXiv (Cornell University)
  31. Aggregated Dense Layer in Squeeze and Excitation Networks
    Mahendran Narayanan · 2024 · Lecture notes in networks and systems
  32. Restructuring, Pruning, and Adjustment of Deep Models for Parallel Distributed Inference
    Afshin Abdi, Saeed Rashidi, Faramarz Fekri, Tushar Krishna · 2020 · arXiv (Cornell University)
  33. Deep Network Shrinkage Applied to Cross-Spectrum Face Recognition
    Christopher Reale, Hyungtae Lee, Heesung Kwon, Rama Chellappa · 2017 · International Conference on Automatic Face and Gesture Recognition
  34. Deep discovery of facial motions using a shallow embedding layer
    Afsane Ghasemi, Mahsa Baktashmotlagh, Simon Denman, Sridha Sridharan, Dung Nguyen Tien, Clinton Fookes · 2017 · Proceedings - International Conference on Image Processing
  35. Machine Learning at the Edge
    Markus Levy, Filip Naiser · 2019 · Elsevier eBooks
  36. Compact Neural Architecture Designs by Tensor Representations
    Jiahao Su, Jingling Li, Xiaoyu Liu, Teresa Ranadive, Christopher Coley, Tai-Ching Tuan, Furong Huang · 2022 · Frontiers in Artificial Intelligence
  37. Adaptive neuron apoptosis for accelerating deep learning on large scale systems
    Charles Siegel, Jeff A. Daily, Abhinav Vishnu · 2016 · IEEE International Conference on Big Data (BigData)
  38. Hierarchical Knowledge Squeezed Adversarial Network Compression
    Peng Li, Chang Shu, Yuan Xie, Yan Qu, Hui Kong · 2020 · Proceedings of the AAAI Conference on Artificial Intelligence
  39. DESIGN SPACE EXPLORATION OF DNNS FOR AUTONOMOUS SYSTEMS
    Jayan Kant Duggal · 2019 · Purdue e-Pubs (Purdue University System)
  40. Sparse Linear Networks with a Fixed Butterfly Structure: Theory and Practice
    Nir Ailon, Omer Leibovich, Vineet Nair · 2020 · arXiv (Cornell University)
  41. PEIPNet: Parametric Efficient Image-Inpainting Network with Depthwise and Pointwise Convolution
    Jaekyun Ko, Wanuk Choi, Sanghwan Lee · 2023 · Sensors
  42. Learning with Scalability and Compactness
    Wenlin Chen · 2016 · Open Scholarship Institutional Repository (Washington University in St. Louis)
  43. Distribution-Aware Binarization of Neural Networks for Sketch Recognition
    Ameya Prabhu, Vishal Batchu, Sri Aurobindo Munagala, Rohit Gajawada, Anoop Namboodiri · 2018 · IEEE Winter Conference on Applications of Computer Vision
  44. Image recognition based on improved convolutional deep belief network model
    Hongmei Wang, Liu Pengzhong · 2020 · Multimedia Tools and Applications
  45. Walsh-Hadamard Variational Inference for Bayesian Deep Learning
    Simone Rossi, Sébastien Marmin, Maurizio Filippone · 2019 · arXiv (Cornell University)
  46. How Not to Give a FLOP: Combining Regularization and Pruning for Efficient Inference
    Tai Vu, Wen, Emily, Roy Nehoran · 2020 · arXiv (Cornell University)
  47. One is Not Enough: Parameter-Efficient Fine-Tuning With Multiplicative Sparse Factorization
    Xuxi Chen, Tianlong Chen, Yu Jian Cheng, Weizhu Chen, Ahmed Hassan Awadallah, Zhangyang Wang · 2024 · IEEE Journal of Selected Topics in Signal Processing
  48. Deep visual embedding for image classification
    Adel Saleh, Mohamed Abdel‐Nasser, Md. Mostafa Kamal Sarker, Vivek Kumar Singh, Saddam Abdulwahab, Nasibeh Saffari, Miguel Ángel García, Domènec Puig · 2018 · International Conference on Innovative Trends in Computer Engineering (ITCE)
  49. TPOT Automated Machine Learning Approach for Multiple Diagnostic Classification of Lung Radiography and Feature Extraction
    Francisco Nauber Bernardo Gois, João Alexandre Lôbo Marques, Simon James Fong · 2023 · Springer eBooks
  50. Efficient Distributed Inference of Deep Neural Networks via Restructuring and Pruning
    A. Abdi, Saeed Rashidi, F. Fekri, Tushar Krishna · 2023 · AAAI Conference on Artificial Intelligence
  51. ELMAENet: A Simple, Effective and Fast Deep Architecture for Image Classification
    Peiju Chang, Jiangshe Zhang, Jinyan Wang, Rongrong Fei · 2019 · Neural Processing Letters
  52. Deep Networks with Adaptive Nyström Approximation
    Luc Giffon, Stéphane Ayache, Thierry Artières, Hachem Kadri · 2019 · International Joint Conference on Neural Networks (IJCNN)
  53. Simplifying Neural Networks via Look up Tables and Product of Sums Matrix Factorizations
    Chai Wah Wu · 2020 · IEEE International Symposium on Circuits and Systems proceedings
  54. McKernel: A Library for Approximate Kernel Expansions in Log-linear Time
    J. de Curtò, I. de Zarzà, Yang, Feng, Alex J. Smola, Fernando De la Torre, Chong‐Wah Ngo, Luc Van Gool · 2017 · arXiv (Cornell University)
  55. Understanding and Training Deep Diagonal Circulant Neural Networks
    Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif C · 2019 · arXiv (Cornell University)
  56. The position-based compression techniques for DNN model
    Minghua Tang, Enrico Russo, Maurizio Palesi · 2023 · The Journal of Supercomputing
  57. Leverage Score Sampling for Complete Mode Coverage in Generative Adversarial Networks
    Joachim Schreurs, Hannes De Meulemeester, Michaël Fanuel, Bart De Moor, Johan A. K. Suykens · 2022 · Lecture notes in computer science
  58. Reducing Parameters of Neural Networks via Recursive Tensor Approximation
    Kyuahn Kwon, Jaeyong Chung · 2022 · Electronics
  59. Residual encoding framework to compress DNN parameters for fast transfer
    Liguo Zhou, Rui Song, Guang Chen, Andreas Festag, Alois Knoll · 2023 · Knowledge-Based Systems
  60. PSM-nets: Compressing Neural Networks with Product of Sparse Matrices
    Luc Giffon, Stéphane Ayache, Hachem Kadri, Thierry Artières, Ronan Sicre · 2021 · International Joint Conference on Neural Networks (IJCNN)
  61. Efficient architecture for deep neural networks with heterogeneous sensitivity
    Hyunjoong Cho, Jinhyeok Jang, Chanhyeok Lee, Seungjoon Yang · 2020 · Neural Networks
  62. A controlled investigation of behaviorally-cloned deep neural network behaviors in an autonomous steering task
    Michael Teti, William Edward Hahn, Shawn Martin, Christopher Teti, Elan Barenholtz · 2021 · Robotics and Autonomous Systems
  63. Kernel-based Translations of Convolutional Networks
    Corinne L. Jones, Roulet, Vincent, Zaïd Harchaoui · 2019 · arXiv (Cornell University)
  64. Separable Layers Enable Structured Efficient Linear Substitutions
    Gavin Douglas Buchanan Gray, Elliot J. Crowley, Amos Storkey · 2019 · arXiv (Cornell University)
  65. Orthogonal Over-Parameterized Training
    Weiyang Liu, Rongmei Lin, Zhen Liu, James Matthew Rehg, Liam Paull, Li Xiong, Le Song, Adrian Weller · 2020 · arXiv (Cornell University)
  66. Kernelized Classification in Deep Networks
    Sadeep Jayasumana, Srikumar Ramalingam, Sanjiv Kumar · 2020 · arXiv (Cornell University)
  67. Is the Number of Trainable Parameters All That Actually Matters?
    Amélie Chatelain, Amine Djeghri, Daniel Hesslow, Julien Launay, Iacopo Poli · 2021 · arXiv (Cornell University)
  68. Automated Digitization of Student’s Marks from the Answer-Book Images Using a Lightweight CNN Model
    Rutul Patel, Neel Patel, Bhupendra D. Fataniya, Dhaval Shah · 2024 · SN Computer Science
  69. Depth-Wise Based Convolutional Neural Network for Street Imagery Digit Number Classification
    Okeke Stephen, Young-Jick Jang, Tae-Soo Yun, Mangal Sain · 2019 · IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC)
  70. Exploiting Non-Linear Redundancy for Neural Model Compression
    Muhammad A. Shah, Raphaël Olivier, Bhiksha Raj · 2021 · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition
  71. Substituting Convolutions for Neural Network Compression
    Elliot J. Crowley, Gavin Douglas Buchanan Gray, Jack Turner, Amos Storkey · 2021 · IEEE Access
  72. New convolutional neural network models for efficient object recognition with humanoid robots
    Simge Nur Aslan, Ayşegül Uçar, Cuneyt Guzelis · 2021 · Journal of Information and Telecommunication
  73. Canonical convolutional neural networks
    Lokesh Veeramacheneni, Moritz Wolter, Reinhard Klein, Jochen Garcke · 2022 · International Joint Conference on Neural Networks (IJCNN)
  74. Towards Adversarial Robustness Via Compact Feature Representations
    Muhammad A. Shah, Raphaël Olivier, Bhiksha Raj · 2021 · IEEE International Conference on Acoustics Speech and Signal Processing
  75. A Survey on Efficient Neural Network Compression Techniques
    Nipun Jain, Medha V. Wyawahare, Vivek Mankar, Tanmay Paratkar · 2023 · Algorithms for intelligent systems
  76. Lite It Fly: An All-Deformable-Butterfly Network
    Rui Lin, Jason Chun Lok Li, Jiajun Zhou, Binxiao Huang, Jie Ran, Ngai Wong · 2023 · IEEE Transactions on Neural Networks and Learning Systems
  77. Binary Separable Convolutional: An Efficient Fast Image Classification Method
    Donglin Jing, Linbo Tang, Yu Rong Pan, Wei Tang, Shichao Zhou · 2019 · IEEE International Conference on Signal, Information and Data Processing (ICSIDP)
  78. Learning and enforcing diversity with Determinantal Point Processes
    Zelda Mariet · 2016 · DSpace@MIT (Massachusetts Institute of Technology)
  79. FeTa: A DCA Pruning Algorithm with Generalization Error Guarantees
    Konstantinos Pitas, Mike E. Davies, Pierre Vandergheynst · 2018 · arXiv (Cornell University)
  80. Efficient and Robust Machine Learning for Real-World Systems
    Franz Pernkopf, Wolfgang Roth, Zoehrer, Matthias, Lukas Pfeifenberger, Schindler, Guenther, Froening, Holger, Sebastian Tschiatschek, Robert Peharz, Matthew Mattina, Zoubin Ghahramani A · 2018 · arXiv (Cornell University)
  81. Revisiting hard thresholding for DNN pruning
    Konstantinos Pitas, Mike E. Davies, Pierre Vandergheynst · 2019 · arXiv (Cornell University)
  82. A novel method to regenerate an optimal CNN by exploiting redundancy patterns in the network
    Sirish Kumar Pasupuleti, Narasinga Rao Miniskar, Vasanthakumar Rajagopal, Raj Narayana Gadde · 2017 · Proceedings - International Conference on Image Processing
  83. Optimization on parametric model
    Fenfen Huang, Wenbin Yao · 2018 · IEEE/IFIP Network Operations and Management Symposium (NOMS)
  84. Deep Asymmetric Networks with a Set of Node-wise Variant Activation Functions
    Jinhyeok Jang, Hyunjoong Cho, Jaehong Kim, Jaeyeon Lee, Seungjoon Yang · 2018 · arXiv (Cornell University)
  85. Optimal Low Rank Tensor Factorization for Deep Learning
    Antra Purohit, Abhishek, Rakesh, Shekhar Verma · 2018 · Communications in computer and information science
  86. Tensor-Solver for Deep Neural Network
    Hantao Huang, Hao Yu · 2018 · Computer architecture and design methodologies
  87. Doctor of Crosswise: Reducing Over-parametrization in Neural Networks
    J. de Curtò, I. de Zarzà, Kris Kitani, Irwin King, Michael Rung-Tsong Lyu · 2019 · arXiv (Cornell University)
  88. Do place cells dream of conditional probabilities? Learning Neural Nyström representations
    Mariano Tepper · 2019 · arXiv (Cornell University)
  89. Training compact deep learning models for video classification using circulant matrices
    Alexandre Araujo, Benjamin Négrevergne, Yann Chevaleyre, Jamal Atif C · 2018 · arXiv (Cornell University)
  90. P-CapsNets: a General Form of Convolutional Neural Networks
    Zhenhua Chen, Xiwen Li, Chuhua Wang, David Crandall · 2019 · arXiv (Cornell University)
  91. Neural Network Pruning for ECG Arrhythmia Classification
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  93. Modeling information flow through deep convolutional neural networks
    Behnaz Nasiri · 2020 · Espace ÉTS (ETS)
  94. Deep Reinforcement Learning with Label Embedding Reward for Supervised Image Hashing
    Zhenzhen Wang, Weixiang Hong, Junsong Yuan · 2020 · arXiv (Cornell University)
  95. Learning deep kernels in the space of monotone conjunctive polynomials
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  96. Towards Applying Deep Learning to the Internet of Things: A Model and a Framework
    Samaa Elnagar, Kweku-Muata Osei-Bryson · 2020 · Lecture notes in business information processing
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