University of Lugano & SUPSI

Lugano, Switzerland

Email: rupesh _at_ idsia _dot_ ch

**19/11/14**: Details of the project I worked on at Microsoft Research this summer are now public! John Platt wrote a nice blog post about it, and a preprint of the paper is available here.**03/11/14**: Our paper on Understanding Locally Competitive Networks has been accepted to the Deep Learning Workshop at NIPS 2014!**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 last year.**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.

In the past, I worked on robust design optimization with Prof. Kalyanmoy Deb.

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

**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

*Last Modified: 19/11/2014*