18/09/14: The winning entry of the Higgs Boson Machine Learning Challenge on Kaggle by Gábor Melis utilized the LWTA activation function proposed by us lastyear.
23/08/14: I just finished a summer internship at Microsoft Research in Redmond, USA.
03/02/14: Check out sheldon.vim, my new collaboration with Engin. It's a fantastic shell-like interpreter for Vim!
05/09/13: Our paper Compete to Compute has been accepted to NIPS 2013. Here is the project page.
I am a researcher in artificial intelligence and machine learning. My supervisor is Prof. Jürgen Schmidhuber. I am currently spending my time understanding artificial neural networks, and their use in the field of Deep Learning.
You may want to have a look at my publications below or my profile on Google Scholar.
H. Fang, S. Gupta, F. Iandola, R. K. Srivastava, L. Deng, P. Dollár, J. Gao, X. He, M. Mitchell, J. Platt, C. L. Zitnick, G. Zweig: From Captions to Visual Concepts and Back. November 18, 2014. arXiv:1411.4952.
R. K. Srivastava, B. R. Steunebrink and J. Schmidhuber: First Experiments with PowerPlay. In: Neural Networks (2013) preprint
R. K. Srivastava, and K. Deb: An Evolutionary Algorithm based Approach to Design Optimization using Evidence Theory. To appear: ASME Journal of Mechanical Design (2013) preprint
R. K. Srivastava, and K. Deb: An Evolutionary based Bayesian Design Optimization Approach under Incomplete Information. Engineering Optimization, Vol. 45, No. 2, pp. 141-165 (2013) preprint
Conferences & Workshops:
R. K. Srivastava, J. Masci, F. Gomez and J. Schmidhuber: Understanding Locally Competitve Networks. NIPS Deep Learning Workshop (2014) arXiv:1410.1165
R. K. Srivastava, J. Masci, S. Kazerounian, F. Gomez, J. Schmidhuber: Compete to Compute. In: Advances in Neural Information Processing Systems (2013) pdf
R. K. Srivastava, B. R. Steunebrink, M. Stollenga and J. Schmidhuber: Continually Adding Self-Invented Problems to the Repertoire: First Experiments with PowerPlay. In: IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL) (2012) pdf
R. K. Srivastava, J. Schmidhuber and F. Gomez: Generalized Compressed Network Search. In: Parallel Problem Solving from Nature, PPSN XII, pp. 337–346 (2012) pdf
R. K. Srivastava, J. Schmidhuber and F. Gomez: Generalized Compressed Network Search. In: Proceedings of the 14th international conference on Genetic and Evolutionary Computation (Late Breaking Abstract), pp. 647–648 (2012) pdf
R. K. Srivastava and K. Deb: An EA-based Approach to Design Optimization using Evidence Theory. In: Proceedings of the 13th annual conference on Genetic and Evolutionary Computation, pp. 1139–1146 (2011) pdf
R. K. Srivastava and K. Deb: Bayesian Reliability Analysis under Incomplete Information using Evolutionary Algorithms. In: 8th International Conference on Simulated Evolution And Learning (SEAL - 2010), Lecture Notes in Computer Science, vol. 6457, pp. 435–444, Springer (2010) pdf
K. Nishijima, Y. Sun, R. K. Srivastava, H. Ogai and B. Bhattacharya: Advanced pipe inspection robot using rotating probe. In: 15th International Symposium on Artificial Life and Robotics, Beppu, Japan, pp. 573–576 (2010) pdf
R. K. Srivastava, J. Masci, S. Kazerounian, F. Gomez and J. Schmidhuber: Compete to Compute. IDSIA Tech Report 2013. pdf
R. K. Srivastava, J. Masci, F. Gomez and J. Schmidhuber: Understanding Locally Competitve Networks. arXiv preprint 2014. arXiv:1410.1165