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1Allegro AI · GitHub
https://github.com/allegroai
4 years ago by @dallmann
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pytorch
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1pytorch-lightning
The lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate - PyTorchLightning/pytorch-lightning
4 years ago by @dallmann
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1microsoft/DeepSpeed: DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.
https://github.com/microsoft/DeepSpeed
5 years ago by @nosebrain
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1Dealing with Pad Tokens in Sequence Models: Loss Masking and PyTorch’s Packed Sequence – Ryan Kresse
http://ryankresse.com/dealing-with-pad-tokens-in-sequence-models-loss-masking-and-pytorchs-packed-sequence/
6 years ago by @dallmann
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4Written Memories: Understanding, Deriving and Extending the LSTM - R2RT
https://r2rt.com/written-memories-understanding-deriving-and-extending-the-lstm.html
6 years ago by @dallmann
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1Smerity.com: Explaining and illustrating orthogonal initialization for recurrent neural networks
Vanishing Gradients in RNN / Eigenvalue Matrix
6 years ago by @dallmann
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1Optimizing Contrastive/Rank/Triplet Loss in Tensorflow for Neural Information Retrieval · Han Xiao Tech Blog
https://hanxiao.github.io/2017/11/08/Optimizing-Contrastive-Rank-Triplet-Loss-in-Tensorflow-for-Neural/
7 years ago by @dallmann
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1Warp loss for implicit feedback recommendation
Blog post describing warp loss
7 years ago by @dallmann
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1GitHub - mutux/ptb_lm: A tutorial of the tutorial of TensorFlow RNN language model ptb_word_lm using CUDNN
ptb_lm - A tutorial of the tutorial of TensorFlow RNN language model ptb_word_lm using CUDNN
7 years ago by @dallmann
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1TensorFlow LSTM benchmark — RETURNN 1.0-dev documentation
http://returnn.readthedocs.io/en/latest/tf_lstm_benchmark.html
7 years ago by @dallmann
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1Kubernets GPU Guide
Kubernetes-GPU-Guide - This guide should help fellow researchers and hobbyists to easily automate and accelerate there deep leaning training with their own Kubernetes GPU cluster.
7 years ago by @dallmann
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1An Overview of ConvNet architectures
https://www.microway.com/download/whitepaper/An_Overview_of_Convolutional_Neural_Network_Architectures_for_Deep_Learning_fall2016.pdf
7 years ago by @dallmann
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deep_learning
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2Neural Network Architectures
https://culurciello.github.io/tech/2016/06/04/nets.html
8 years ago by @dallmann
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cnn
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1Keras - Seq2Seq Model (Github)
Repository of advanced Seq2Seq Learning models for Keras
8 years ago by @dallmann
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2Embedding Methods for NLP
http://emnlp2014.org/tutorials/8_notes.pdf
8 years ago by @dallmann
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embeddings
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1A guide to convolution arithmetic for deep learning
https://arxiv.org/pdf/1603.07285v1.pdf
8 years ago by @dallmann
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convolution
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1Attention and Augmented Recurrent Neural Networks — Distill
http://distill.pub/2016/augmented-rnns/
8 years ago by @dallmann
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1Deep Learning For Image Understanding In Planetary Science | Parallel Forall
Leon Palafox shares how he utilizes cuDNN through MatConvNet for processing images of Mars on NVIDIA Quadro K5000 graphics cards
8 years ago by @dallmann
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9Understanding LSTM Networks -- colah's blog
http://colah.github.io/posts/2015-08-Understanding-LSTMs/
8 years ago by @dallmann
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2Neural Networks, Types, and Functional Programming -- colah's blog
http://colah.github.io/posts/2015-09-NN-Types-FP/
8 years ago by @dallmann
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publications (hide)182
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4Sequential Item Recommendation in the MOBA Game Dota 2
A. Dallmann, J. Kohlmann, D. Zoller, and A. Hotho. 2021 International Conference on Data Mining Workshops (ICDMW), page 10-17. (December 2021)
2 years ago by @dallmann
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myown
dota
recommendation
deep_learning
sir
myowndotarecommendationdeep_learningsir
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5Contextual Sequence Modeling for Recommendation with Recurrent Neural Networks
E. Smirnova, and F. Vasile. Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems, ACM, (August 2017)
2 years ago by @dallmann
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rnn
recommendation
context
deep_learning
lstm
rnnrecommendationcontextdeep_learninglstm
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6What to Do Next: Modeling User Behaviors by Time-LSTM.
Y. Zhu, H. Li, Y. Liao, B. Wang, Z. Guan, H. Liu, and D. Cai. (2017)
2 years ago by @dallmann
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recommendation
deep_learning
time
lstm
recommendationdeep_learningtimelstm
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8Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks.
M. Quadrana, A. Karatzoglou, B. Hidasi, and P. Cremonesi. CoRR, (2017)
3 years ago by @dallmann
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rnn
thema:ba
thema:perso
personalization
thema
recommendation
deep_learning
rnnthema:bathema:persopersonalizationthemarecommendationdeep_learning
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7A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models
A. Dallmann, D. Zoller, and A. Hotho. Fifteenth ACM Conference on Recommender Systems, ACM, (September 2021)
3 years ago by @dallmann
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myown
recommender_systems
evaluation
deep_learning
information_retrieval
research:recommender
research:recommender:selected
myownrecommender_systemsevaluationdeep_learninginformation_retrievalresearch:recommenderresearch:recommender:selected
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2On Estimating Recommendation Evaluation Metrics under Sampling
R. Jin, D. Li, B. Mudrak, J. Gao, and Z. Liu. (2021)cite arxiv:2103.01474.
3 years ago by @dallmann
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sampling
recommendation
deep_learning
samplingrecommendationdeep_learning
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7Neural Collaborative Filtering.
X. He, L. Liao, H. Zhang, L. Nie, X. Hu, and T. Chua. WWW, page 173-182. ACM, (2017)
3 years ago by @dallmann
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recommendation
deep_learning
recommendationdeep_learning
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6Sequential Recommendation with User Memory Networks
X. Chen, H. Xu, Y. Zhang, J. Tang, Y. Cao, Z. Qin, and H. Zha. Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, (2018)
3 years ago by @dallmann
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memory_networks
deep_learning
sequential_recommendation
memory_networksdeep_learningsequential_recommendation
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4DeepMove: Predicting Human Mobility with Attentional Recurrent Networks
J. Feng, Y. Li, C. Zhang, F. Sun, F. Meng, A. Guo, and D. Jin. Proceedings of the 2018 World Wide Web Conference, (2018)
3 years ago by @dallmann
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mobility
sequence_modeling
deep_learning
mobilitysequence_modelingdeep_learning
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3Recurrent Convolutional Neural Network for Sequential Recommendation
C. Xu, P. Zhao, Y. Liu, J. Xu, V. S.Sheng, Z. Cui, X. Zhou, and H. Xiong. The World Wide Web Conference, page 3398–3404. New York, NY, USA, Association for Computing Machinery, (2019)
4 years ago by @dallmann
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sequential_item
rnn
cnn
recommendation
deep_learning
sequential_itemrnncnnrecommendationdeep_learning
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5Convolutional Self-Attention Networks
B. Yang, L. Wang, D. Wong, L. Chao, and Z. Tu. NAACL-HLT, (2019)
4 years ago by @dallmann
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convnet
self_attention
attention
deep_learning
convnetself_attentionattentiondeep_learning
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10Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
J. Tang, and K. Wang. Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, (2018)
4 years ago by @dallmann
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thema:convrec
sequence_modeling
convolution
thema
deep_learning
sequential_recommendation
thema:convrecsequence_modelingconvolutionthemadeep_learningsequential_recommendation
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3CosRec: 2D Convolutional Neural Networks for Sequential Recommendation
A. Yan, S. Cheng, W. Kang, M. Wan, and J. McAuley. Proceedings of the 28th ACM International Conference on Information and Knowledge Management, (2019)
4 years ago by @dallmann
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sequence_modeling
convolution
deep_learning
sequential_recommendation
sequence_modelingconvolutiondeep_learningsequential_recommendation
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4A Simple Convolutional Generative Network for Next Item Recommendation
F. Yuan, A. Karatzoglou, I. Arapakis, J. Jose, and X. He. Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, (2019)
4 years ago by @dallmann
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sequence_modeling
convolution
deep_learning
sequential_recommendation
sequence_modelingconvolutiondeep_learningsequential_recommendation
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5Convolutional Self-Attention Networks
B. Yang, L. Wang, D. Wong, L. Chao, and Z. Tu. NAACL-HLT, (2019)
4 years ago by @dallmann
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sequence_modeling
self_attention
convolution
deep_learning
sequence_modelingself_attentionconvolutiondeep_learning
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4An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
S. Bai, J. Kolter, and V. Koltun. (2018)cite arxiv:1803.01271.
4 years ago by @dallmann
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cnn
sequence_modeling
deep_learning
cnnsequence_modelingdeep_learning
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3Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences
D. Neil, M. Pfeiffer, and S. Liu. NIPS, (2016)
4 years ago by @dallmann
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rnn
time_gate
dwell_time
deep_learning
lstm
rnntime_gatedwell_timedeep_learninglstm
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6What to Do Next: Modeling User Behaviors by Time-LSTM.
Y. Zhu, H. Li, Y. Liao, B. Wang, Z. Guan, H. Liu, and D. Cai. IJCAI, page 3602-3608. ijcai.org, (2017)
4 years ago by @dallmann
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rnn
time_gate
dwell_time
deep_learning
rnntime_gatedwell_timedeep_learning
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2JUMP: a Jointly Predictor for User Click and Dwell Time
T. Zhou, H. Qian, Z. Shen, C. Zhang, C. Wang, S. Liu, and W. Ou. IJCAI, (2018)
4 years ago by @dallmann
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dwell_time
deep_learning
dwell_timedeep_learning
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2Distanced LSTM: Time-Distanced Gates in Long Short-Term Memory Models for Lung Cancer Detection
R. Gao, Y. Huo, S. Bao, Y. Tang, S. Antic, E. Epstein, A. Balar, S. Deppen, A. Paulson, K. Sandler and 2 other author(s). MLMI@MICCAI, (2019)
4 years ago by @dallmann
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dwell_time
deep_learning
dwell_timedeep_learning
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