Rupesh Kumar Srivastava

PhD candidate @ IDSIA
University of Lugano & SUPSI
Lugano, Switzerland
Email: rupesh _at_ idsia _dot_ ch

I am a PhD student studying artificial intelligence and machine learning, supervised by Prof. Jürgen Schmidhuber at IDSIA. I am currently spending my time understanding and improving artificial neural networks.

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

You may want to have a look at my publications below or my profile on Google Scholar.


Recent Updates


Publications

Under Review:

LSTM: A Search Space Odyssey
K. Greff, R. K. Srivastava, J. Koutník, B. R. Steunebrink and J. Schmidhuber
arXiv:1503.04069

Conferences & Workshops:

Training Very Deep Networks
R. K. Srivastava, K. Greff and J. Schmidhuber
Neural Information Processing Systems (NIPS 2015 Spotlight) arXiv:1507.06228

Highway Networks
R. K. Srivastava, K. Greff and J. Schmidhuber
Deep Learning Workshop (ICML 2015). arXiv:1505.00387 poster

Understanding Locally Competitve Networks
R. K. Srivastava, J. Masci, F. Gomez and J. Schmidhuber
International Conference on Learning Representations (ICLR 2015 Conference Track) arXiv:1410.1165
Previously presented at the NIPS 2014 Deep Learning Workshop.

From Captions to Visual Concepts and Back
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
IEEE International Conference on Computer Vision and Patter Recognition (CVPR 2015). arXiv:1411.4952

Compete to Compute
R. K. Srivastava, J. Masci, S. Kazerounian, F. Gomez and J. Schmidhuber
Neural Information Processing Systems (NIPS 2013) pdf

Continually Adding Self-Invented Problems to the Repertoire: First Experiments with PowerPlay
R. K. Srivastava, B. R. Steunebrink, M. Stollenga and J. Schmidhuber
IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL 2012) pdf

Generalized Compressed Network Search
R. K. Srivastava, J. Schmidhuber and F. Gomez
Parallel Problem Solving from Nature (PPSN 2012) pdf
Previously presented as a GECCO 2012 Late Breaking Abstract.

An EA-based Approach to Design Optimization using Evidence Theory
R. K. Srivastava and K. Deb
Conference on Genetic and Evolutionary Computation (GECCO 2011) pdf

Bayesian Reliability Analysis under Incomplete Information using Evolutionary Algorithms
R. K. Srivastava and K. Deb
Simulated Evolution And Learning (SEAL 2010) pdf

Advanced pipe inspection robot using rotating probe
K. Nishijima, Y. Sun, R. K. Srivastava, H. Ogai and B. Bhattacharya
International Symposium on Artificial Life and Robotics (AROB 2010) pdf

Journals:

First Experiments with PowerPlay
R. K. Srivastava, B. R. Steunebrink and J. Schmidhuber
Neural Networks (2013) preprint

An Evolutionary Algorithm based Approach to Design Optimization using Evidence Theory
R. K. Srivastava, K. Deb and R. Tulshyan
ASME Journal of Mechanical Design (2013) preprint

An Evolutionary based Bayesian Design Optimization Approach under Incomplete Information
R. K. Srivastava and K. Deb
Engineering Optimization (2013) preprint

Reports:

Compete to Compute
R. K. Srivastava, J. Masci, S. Kazerounian, F. Gomez and J. Schmidhuber
IDSIA Tech Report 2013 pdf


Last Modified: 20/09/2015