Balaraman Ravindran

Recently there has been a lot of interest in learning common representations for multiple views of data. These views could belong to different modalities or languages. Typically, such common representations are learned using a parallel corpus between the two views (say, 1M images and their English captions). In this work, we address a real-world scenario where no direct parallel data is available between two views of interest (say, V1 and V2) but parallel data is available between each of these views and a pivot view (V3). We propose a model for learning a common representation for V1, V2 and V3 using only the parallel data available between V1V3 and V2V3. The proposed model is generic and even works when there are n views of interest and only one pivot view which acts as a bridge between them. There are two specific downstream applications that we focus on (i) Transfer learning between languages L1,L2,…,Ln using a pivot language L and (ii) cross modal access between images and a language L1 using a pivot language L2. We evaluate our model using two datasets : (i) publicly available multilingual TED corpus and (ii) a new multilingual multimodal dataset created and released as a part of this work. On both these datasets, our model outperforms state of the art approaches.

Joint work with Janarthanan R., Sarath Chandar A. P., and Mitesh Khapra. Appeared at NAACL 2016.

Prof. Ravindran is currently an Professor in Computer Science at IIT Madras. He has nearly two decades of research experience in machine learning and specifically reinforcement learning. Currently his research interests are centered on learning from and through interactions and span the areas of data mining, social network analysis, and reinforcement learning.

He is the co-director of the reconfigurable and intelligent systems engineering (RISE) group at IIT Madras, which has nearly 80 members associated with it currently. He also heads the Interdisciplinary Laboratory for Data Sciences at IIT Madras, which spans six Departments and looks at analytics in many different disciplines.
He had been the Program Chair for ADCOM 2013.