View the Call for Papers in PDF form here.

Call for Papers

Short papers are solicited for the 1st Indian Workshop on Machine Learning. Areas of interest to the workshop include all areas of machine learning - both foundational as well as applied, including, but not limited to:

• Learning algorithms: Bayesian learning, graphical models, deep learning, kernel and other non-parametric methods, approximate inference, neural networks, dimensionality reduction, optimization.
• Applications: applications of machine learning techniques to areas such as natural language processing,text analysis, computer vision, systems biology, web and social network analysis and data mining.
• Reinforcement learning: online learning, planning, decision and control, Markov decision processes, multi-agent systems.
• Theory: statistical learning theory, generalization error bounds, lower bounds or hardness results.
• Signal processing: coding, denoising, segmentation, sparse recovery, source separation.

Submission Instructions: Instructions for submission can be found on the iWML 2013 website here.

Dual Submissions Policy: Since the workshop is not intended to have a proceedings comprising full versions of the papers, concurrent submissions to other venues are acceptable provided that the concurrent submission or intention to submit to other venues is declared to all venues including iWML.

Reviewing Policy: Submissions shall be refereed on the basis of technical quality, potential impact, and clarity. A fraction of the submitted papres shall be accepted for presentation at the workshop. One author of each accepted paper will be required to attend the workshop to present the work.

Student Participation: In order to encourage graduate students working in machine learning to interact with the machine learning research community in India we propose to invite some students to attend the workshop (this is in addition to students who would be attending the workshop to present their work). In order to apply for participation in the workshop, students should apply online along with a letter of recommendation (typically from their thesis supervisor). The details of the application procedure are given on the workshop website here.