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Poster Session
Jaleh Zand · Kun Tu · Michael (Tao-Yi) Lee · Ian Covert · Daniel Hernandez · Zahra Ebrahimzadeh · Joanna Slawinska · Akara Supratak · Miao Lu · John Alberg · Dennis Shen · Serene Yeo · Hsing-Kuo K Pao · Kian Ming Adam Chai · Anish Agarwal · Dimitrios Giannakis · Muhammad Amjad

Fri Dec 08 11:45 AM -- 12:30 PM (PST) @
in NIPS 2017 Time Series Workshop »

Feel free to enjoy posters at lunch time as well!

Víctor Campos, Brendan Jou, Xavier Giró-I-Nieto, Jordi Torres and Shih-Fu Chang. Skip RNN: Learning to Skip State Updates in Recurrent Neural Networks.

Yao-Hung Hubert Tsai, Han Zhao, Nebojsa Jojic and Ruslan Salakhutdinov. DISCOVERING ORDER IN UNORDERED DATASETS: GENERATIVE MARKOV NETWORKS.

Yaguang Li, Rose Yu, Cyrus Shahabi and Yan Liu. Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting.

Alex Tank, Emily Fox and Ali Shojaie. An Efficient ADMM Algorithm for Structural Break Detection in Multivariate Time Series.

Hossein Soleimani, James Hensman and Suchi Saria. Scalable Joint Models for Reliable Event Prediction.

Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai and Akiko Takeda. Learning theory and algorithms for shapelets and other local features.

Tao-Yi Lee, Yuh-Jye Lee, Hsing-Kuo Pao, You-Hua Lin and Yi-Ren Yeh. Elastic Motif Segmentation and Alignment of Time Series for Encoding and Classification.

Yun Jie Serene Yeo, Kian Ming A. Chai, Weiping Priscilla Fan, Si Hui Maureen Lee, Junxian Ong, Poh Ling Tan, Yu Li Lydia Law and Kok-Yong Seng. DP Mixture of Warped Correlated GPs for Individualized Time Series Prediction.

Anish Agarwal, Muhammad Amjad, Devavrat Shah and Dennis Shen. Time Series Forecasting = Matrix Estimation.

Rose Yu, Stephan Zheng, Anima Anandkumar and Yisong Yue. Long-term Forecasting using Tensor-Train RNNs.

Pranamesh Chakraborty, Chinmay Hegde and Anuj Sharma. Trend Filtering in Network Time Series with Applications to Traffic Incident Detection.

Jaleh Zand and Stephen Roberts. MiDGaP: Mixture Density Gaussian Processes.

Dimitrios Giannakis, Joanna Slawinska, Abbas Ourmazd and Zhizhen Zhao. Vector-Valued Spectral Analysis of Space-Time Data.

Ruofeng Wen, Kari Torkkola and Balakrishnan Narayanaswamy. A Multi-Horizon Quantile Recurrent Forecaster.

Alessandro Davide Ialongo, Mark van der Wilk and Carl Edward Rasmussen. Closed-form Inference and Prediction in Gaussian Process State-Space Models.

Hao Liu, Haoli Bai, Lirong He and Zenglin Xu. Structured Inference for Recurrent Hidden Semi-markov Model.

Petar Veličković, Laurynas Karazija, Nicholas Lane, Sourav Bhattacharya, Edgar Liberis, Pietro Lio, Angela Chieh, Otmane Bellahsen and Matthieu Vegreville. Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data.

Kun Tu, Bruno Ribeiro, Ananthram Swami and Don Towsley. Temporal Clustering in time-varying Networks with Time Series Analysis.

Shaojie Bai, J. Zico Kolter and Vladlen Koltun. Convolutional Sequence Modeling Revisited.

Apurv Shukla, Se-Young Yun and Daniel Bienstock. Non-Stationary Streaming PCA.

Kun Zhao, Takayuki Osogami and Rudy Raymond. Fluid simulation with dynamic Boltzmann machine in batch manner.

Anderson Zhang, Miao Lu, Deguang Kong and Jimmy Yang. Bayesian Time Series Forecasting with Change Point and Anomaly Detection.

Akara Supratak, Steffen Schneider, Hao Dong, Ling Li and Yike Guo. Towards Desynchronization Detection in Biosignals.

Rudy Raymond, Takayuki Osogami and Sakyasingha Dasgupta. Dynamic Boltzmann Machines for Second Order Moments and Generalized Gaussian Distributions.

Itamar Ben-Ari and Ravid Shwartz-Ziv. Sequence modeling using a memory controller extension for LSTM.

Neil Dhir and Adam Kosiorek. Bayesian delay embeddings for dynamical systems.

Aleksander Wieczorek and Volker Roth. Time Series Classification with Causal Compression.

Daniel Hernandez, Liam Paninski and John Cunningham. Variational inference for latent nonlinear dynamics.

Alex Tank, Ian Covert, Nick Foti, Ali Shojaie and Emily Fox. An Interpretable and Sparse Neural Network Model for Nonlinear Granger Causality Discovery.

John Alberg and Zachary Lipton. Improving Factor-Based Quantitative Investing by Forecasting Company Fundamentals.

Achintya Kr. Sarkar and Zheng-Hua Tan. Time-Contrastive Learning Based DNN Bottleneck Features for Text-Dependent Speaker Verification.

Ankit Gandhi, Vineet Chaoji and Arijit Biswas. Modeling Customer Time Series for Age Prediction.

Zahra Ebrahimzadeh and Samantha Kleinberg. Multi-Scale Change Point Detection in Multivariate Time Series.

Author Information

Jaleh Zand (University of Oxford)
Kun Tu (Univ. of Massachusetts Amherst)
Michael (Tao-Yi) Lee (National Taiwan University)
Ian Covert (University of Washington)
Daniel Hernandez (Columbia University)
Zahra Ebrahimzadeh (Stevens Institute of Technology)
Joanna Slawinska (University of Wisconsin-Milwaukee)
Akara Supratak (Imperial College London)
Miao Lu (Yahoo Research)
John Alberg (Euclidean Technologies, Inc)
Dennis Shen (Massachusetts Institute of Technology)
Serene Yeo (DSO National Laboratories)
Hsing-Kuo K Pao (National Taiwan University of Science and Technology)
Kian Ming Adam Chai (DSO National Laboratories)
Anish Agarwal (MIT)
Dimitrios Giannakis (New York University)
Muhammad Amjad (MIT)

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