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Title:

Learning Transferable Features with Deep Adaptation Networks

Abstract:

Learning Transferable Features with Deep Adaptation Networks

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# Title Author Topic Medium Score
1 Performance guarantees for transferring representations Daniel McNamara 978 survey 34.60
2 Awesome - Most Cited Deep Learning Papers Terry Taewoong Um 713 resource 31.50
3 Current & Future NLP Research A Few Random Remarks Jason Eisner 311 lecture 30.18
4 An Overview of Multi-Task Learning in Deep Neural Networks Sebastian Ruder 829 tutorial 27.46
5 AutoML for large scale image classification and object detection Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc Le tutorial 26.29
6 Transfer Learning Andrej Karpathy 713 tutorial 26.18
7 Introducing state of the art text classification with universal language models Jeremy Howard, Sebastian Ruder 542 resource 25.38
8 Deep Learning Ian Goodfellow and Yoshua Bengio and Aaron Courville 711 survey 24.80
9 Image Recognition Goku Mohandas 713 tutorial 24.63
10 Multilingual Sentiment and Subjectivity Analysis Rada Mihalcea, Carmen Banea, Janyce Wiebe 381 tutorial 24.34
11 Transfer Learning - Machine Learnings Next Frontier Sebastian Ruder 978 tutorial 24.01
12 Deep Learning for Natural Language Processing Tianchuan Du, Vijay K. Shanker 711 survey 23.60
13 Deep Learning for Natural Language Processing and Machine Translation Kevin Duh 451 tutorial 23.45
14 Distinguishing Past, On-going, and Future Events: The EventStatus Corpus Ruihong Huang, Ignacio Cases, Dan Jurafsky, Cleo Condoravdi, Ellen ... 999 paper 23.39
15 Correlation Alignment for Domain Adaptation Baochen Sun, Jiashi Feng, Kate Saenko 426 library 23.35
16 Mathematics of Deep Learning Raja Giryes, René Vidal 713 tutorial 23.22
17 Networks, Reinforcement, Relational, Recurrent, Learning Petar Velickovic tutorial 23.18
18 CS 294: Deep Reinforcement Learning Sergey Levine, John Schulman, Chelsea Finn 857 resource 23.15
19 Deep Learning Reading List Caglar Gulcehre 711 resource 23.15
20 Deep Learning Reading List Caglar Gulcehre 711 tutorial 23.15
21 Deep Reinforcement Learning: An Overview Yuxi Li 857 resource 22.99
22 Meta-Learning Joaquin Vanschoren 851 survey 22.80
23 An Overview of Proxy-label Approaches for Semi-supervised Learning Sebastian Ruder 581 resource 22.78
24 Deep multi-task learning with low level tasks supervised at lower layers Anders Søgaard, Yoav Goldberg 999 paper 22.66
25 Multi-domain Neural Network Language Generation for Spoken Dialogue Systems Tsung-Hsien Wen, Milica Gaši?, Nikola Mrkši?, Lina M. Rojas-Barahon... 999 paper 22.65
26 Deep Learning for Dialogue Systems Yun-Nung (Vivian) Chen, Asli Celikyilmaz, Dilek Hakkani-Tur 756 tutorial 22.61
27 Deep Learning for Conversational AI Pei-Hao Su, Nikola MrköiÊ, Iñigo Casanueva, Ivan VuliÊ 811 tutorial 22.55
28 Top 10 IPython Notebook Tutorials for Data Science and Machine Learning Matthew Mayo 107 resource 22.41
29 State-of-the-art Result for all Machine Learning Problems Reddit Sota 711 library 22.37
30 Convolutional Neural Networks (for NLP) Richard Socher 744 lecture 22.11
31 NLP's ImageNet moment has arrived Sebastian Ruder 862 resource 22.06
32 Speaker ID I Javier Hernando 944 tutorial 21.98
33 PyTorch-GAN Jun-Yan Zhu, Richard Zhang, Deepak Pathak, Trevor Darrell, Alexei A... 731 library 21.90
34 A survey of transfer learning Karl Weiss, Taghi M. Khoshgoftaar and DingDing Wang 978 resource 21.75
35 Multimodal Deep Learning Xavier Giro-i-Nieto 713 tutorial 21.67
36 Optimization as a Model for Few-Shot Learning Hugo Larochelle tutorial 21.65
37 Parametric Speech Synthesis Antonio Bonafonte 945 tutorial 21.63
38 Domain Adaptation John Blitzer, Hal Daume III 999 tutorial 21.55
39 Deep Learning for Dialogue Systems Yun-Nung (Vivian) Chen, Asli Celikyilmaz, Dilek Hakkani-Tur 445 tutorial 21.50
40 Pretrained ConvNets for pytorch Remi Cadene library 21.39
41 Representations for Language: From Word Embeddings to Sentence Meanings Christopher Manning 721 tutorial 21.30
42 Representations for Language: From Word Embeddings to Sentence Meanings Christopher Manning 721 tutorial 21.30
43 Deep Learning for Speech/Language Processing Li Deng 863 tutorial 20.93
44 BAIR Retreat 3/28/17 Trevor Darrell 713 survey 20.83
45 Neural Components In Statistical Machine Translation Author Unknown survey 20.81
46 An Introduction to Transfer Learning and Domain Adaptation Amaury Habrard 978 survey 20.80
47 Convolutional Neural Networks for Sentence Classification Yoon Kim 999 paper 20.72
48 Gans Awesome Applications Minchul Shin 811 resource 20.63
49 A Brief Introduction to Deep Learning Yangyan Li 711 tutorial 20.63
50 Practical Neural Machine Translation Haddow Sennrich 753 tutorial 20.63