Publications

Conference

• A Stochastic Differential Equation Framework for Guiding Online User Activities in Closed Loop
  Yichen Wang, Evangelos Theodorou, Apurv Verma, and Le Song
  the 21st Annual Conference on Artificial Intelligence and Statistics (AISTATS), 2018.

• Predicting User Activity Level in Point Processes with Mass Transport Equation
  Yichen Wang, Xiaojing Ye, Hongyuan Zha, and Le Song
  the 31st Annual Conference on Neural Information Processing Systems (NIPS), 2017.

• Variational Policy for Guiding Point Processes
  Yichen Wang, Grady Williams, Evangelos Theodorou, and Le Song
  the 34th International Conference on Machine Learning (ICML), 2017 (Oral).

• Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
  Rakshit Trivedi, Hanjun Dai, Yichen Wang, and Le Song
  the 34th International Conference on Machine Learning (ICML), 2017 (Oral).

• Linking Micro Event History to Macro Prediction in Point Process Models
  Yichen Wang, Xiaojing Ye, Haomin Zhou, Hongyuan Zha, and Le Song
  the 20th Annual Conference on Artificial Intelligence and Statistics (AISTATS), 2017.

• Isotonic Hawkes Processes
  Yichen Wang, Bo Xie, Nan Du, and Le Song
  the 33rd International Conference on Machine Learning (ICML), 2016 (Oral).
       A nonlinear Hawkes process model with an efficient algorithm to learn both the link function and weights parameters

• Coevolutionary Latent Feature Processes for Continuous-Time User-Item Interactions
  Yichen Wang, Nan Du, Rakshit Trivedi, and Le Song
  the 30th Annual Conference on Neural Information Processing Systems (NIPS), 2016.
       A scalable point process model capturing the coevolution phenomena of user and item latent features

• Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics
  Yichen Wang, Robert Chen, Joydeep Ghosh, Joshua Denny, Abel Kho, You Chen, Bradley Malin, and Jimeng Sun
  the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015, (Oral).
  [Code]

• Detecting Emotions in Social Media: A Constrained Optimization Approach [IBM Press]
  Yichen Wang and Aditya Pal
  the 24th International Joint Conferences on Artificial Intelligence (IJCAI), 2015, (Oral).
  [Code]

• COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution
  Mehrdad Farajtabar, Yichen Wang, Manuel Gomez-Rodriguez, Shuang Li, Hongyuan Zha and Le Song
  the 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015. (Oral, acceptance rate: 15/1838 = 0.8%)

• Time-Sensitive Recommendation From Recurrent User Activities
  Nan Du, Yichen Wang, Niao He and Le Song
  the 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015.

Journal

• COEVOLVE: A Joint Point Process Model for Information Diffusion and Network Co-evolution
  Mehrdad Farajtabar, Yichen Wang, Manuel Gomez-Rodriguez, Shuang Li, Hongyuan Zha and Le Song
  Journal of Machine Learning Research, 2017

Workshop

• Recurrent Coevolutionary Feature Embedding Processes for Recommendation
  Hanjun Dai*, Yichen Wang*, Rakshit Trivedi, and Le Song (*Equal contributions)
  the 1st Workshop on Deep Learning for Recommendation Systems, RecSys, 2016 (Best Paper)

Preprints

• Deep Coevolutionary Network: Embedding User and Item Features for Recommendation
  Hanjun Dai*, Yichen Wang*, Rakshit Trivedi, and Le Song (*Equal contributions)

• Fast and Simple Optimization for Poisson Likelihood Models
  Niao He, Zaid Harchaoui, Yichen Wang, and Le Song