Rutgers Machine Learning Group

Publications
  • Learning Single-View 3D Reconstruction with Adversarial Training
    P. Pinheiro, N. Rostamzadeh, S. Ahn
    [ArXiv18][pdf]
  • Reinforced Imitation Learning from Observations
    K. Żołna, N. Rostamzadeh, Y. Bengio, S. Ahn+, P. Pinheiro+  (+ indicates equal advising)
    [NeurIPS 18 Workshop on Imitation Learning and Its Challenges in Robotics] [pdf]

  • Bayesian Model-Agnostic Meta-Learning
    T Kim*, J Yoon*, O. Dia, S. Kim, Y. BengioS. Ahn  
    [* indicates equal contribution]
    [NeurIPS18] [pdfSpotlight (top 3.5% = 168/4856)

  • Hierarchical Multiscale Recurrent Neural Networks
    J. Chung, S. AhnY. Bengio
    [ICLR17] [pdf]

  • Denoising Criterion for Variational Auto-Encoding Framework 
    D. Im, S. Ahn, R. Memisevic, Y. Bengio
    [AAAI17] [pdf]

  • SENA: Preserving Social Structure for Network Embedding 
  • S. Hong, T. Chakraborty, S. Ahn, G. Husari and N. Park 
    2017, ACM Conference on Hypertext and Social Media

  • A Neural Knowledge Language Model
    S. Ahn, H. Choi, T. Parnamaa, Y. Bengio
    [ArXiv16] [pdf] [dataset]

  • Hierarchical Memory Networks
    S. Chandar, S. Ahn, H. Larochelle, P. Vincent, G. Tasauro, Y. Bengio
    [ArXiv16] [pdf]

  • Learning Latent Multiscale Structure using Recurrent Neural Networks
    J. Chung, S. AhnY. Bengio
    NIPS 2016 Workshop on Neural Abstract Machines & Program Induction (NAMPI)

  • Pointing the Unknown Words 
    C. Gulcehre, S. Ahn, R. Nallapati, B. Zhou, Y. Bengio.
    [ACL16] [pdf]

  • Generating Factoid Questions with Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus
    I. V. Serban*, A. G. Duran*, C. Gulcehre, S. Ahn, S. Chandar, A. Courville, Y. Bengio 
    (* Equal contribution)
    [ACL16] [pdf] [dataset

  • Scalable MCMC for Mixed Membership Stochastic Blockmodels 
    W. Li*S. Ahn*, and M. Welling (* Equal contribution)
    [AISTATS16] [pdf

  • Scalable Overlapping Community Detection
    I. El-Helw, R. Hofman, W. Li, S. Ahn, M. Welling, H. Bal
  • [ParLearning16] [pdfBest Paper Award

  • Stochastic Gradient MCMC: Algorithms and Applications 
    [PhD Dissertation 15] [pdf]

  • Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC
    S. Ahn, A. Korattikara, N. Liu, S. Rajan, and M. Welling
    [KDD15] [pdf] (Acceptance Rate: 19%)

  • Distributed Stochastic Gradient MCMC
    S. Ahn, B. Shahbaba, and M. Welling
    [ICML14] [pdf

  • Distributed and Adaptive Darting Monte Carlo through Regenerations
    S. Ahn, Y. Chen, and M. Welling
    [AISTATS13] [pdf

  • Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring
    S. Ahn, A. Korattikara, and M. Welling
    [ICML12] [pdfBest Paper Award

  • Proactive Context-Aware Sensor Networks 
    S. Ahn and D. Kim
    [EWSN06] (Acceptance Rate: 15%)