Blockout: Dynamic Model Selection for Hierarchical Deep Networks

Blockout: Dynamic Model Selection for Hierarchical Deep Networks

16 December 2015

Papers citing "Blockout: Dynamic Model Selection for Hierarchical Deep Networks"

10 / 10 papers shown

Title
Hadamard product in deep learning: Introduction, Advances and Challenges Grigorios G. Chrysos Yongtao Wu Razvan Pascanu Philip Torr V. Cevher AAML 98 1 0 17 Apr 2025
LEURN: Learning Explainable Univariate Rules with Neural Networks Çağlar Aytekin FAtt 29 0 0 27 Mar 2023
Neural Networks are Decision Trees Çağlar Aytekin FAtt 32 24 0 11 Oct 2022
Visualizing Classification Structure of Large-Scale Classifiers B. Alsallakh Zhixin Yan Shabnam Ghaffarzadegan Zeng Dai Liu Ren FAtt 20 1 0 12 Jul 2020
NBDT: Neural-Backed Decision Trees Alvin Wan Lisa Dunlap Daniel Ho Jihan Yin Scott Lee Henry Jin Suzanne Petryk Sarah Adel Bargal Joseph E. Gonzalez 13 99 0 01 Apr 2020
Attentive Single-Tasking of Multiple Tasks Kevis-Kokitsi Maninis Ilija Radosavovic Iasonas Kokkinos 77 245 0 18 Apr 2019
Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges Di Feng Christian Haase-Schuetz Lars Rosenbaum Heinz Hertlein Claudius Gläser Fabian Duffhauss W. Wiesbeck Klaus C. J. Dietmayer 3DPC 41 988 0 21 Feb 2019
Connectivity Learning in Multi-Branch Networks Karim Ahmed Lorenzo Torresani 24 26 0 27 Sep 2017
Sparse Autoencoder for Unsupervised Nucleus Detection and Representation in Histopathology Images L. Hou Vu Nguyen Dimitris Samaras Tahsin M. Kurc Yi Gao Tianhao Zhao Joel H. Saltz MedIm 35 143 0 03 Apr 2017
Improving neural networks by preventing co-adaptation of feature detectors Geoffrey E. Hinton Nitish Srivastava A. Krizhevsky Ilya Sutskever Ruslan Salakhutdinov VLM 266 7,639 0 03 Jul 2012