You have found Clemens Rosenbaum's web site. I am a PhD candidate at the College of Information and Computer Sciences at the University of Massachusetts Amherst, where I am advised by Sridhar Mahadevan.
My interests span several machine learning disciplines, in particular deep learning and reinforcement learning.

About me and my interests

I am interested in a subfield of artificial intelligence called 'machine learning', the automated discovery of models to solve particular problems. My research focuses on deep learning and reinforcement learning.

Currently, I try to use these approaches to learn models that incorporate long-term memory, i.e. that are able to remember facts or events for an arbitrary amount of time. My go-to example is dialogue, where the (probably) best-known applications of artificial dialog agents include 'intelligent assistants' such as Amazon's Alexa, Apple's Siri, Google's Now, and Microsoft's Cortana.

A very short CV:

Selected Papers

  • Clemens Rosenbaum, Tim Klinger, and Matthew Riemer "Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning" (arxiv 2017)
  • Marlos C. Machado, Clemens Rosenbaum, Xiaoxiao Guo, Miao Liu, Gerald Tesauro, and Murray Campbell, "Eigenoption Discovery through the Deep Successor Representation" (arxiv, 2017)
  • Clemens Rosenbaum, Tian Gao, and Tim Klinger, "e-QRAQ: A Multi-turn Reasoning Dataset and Simulator with Explanations" (WHI@ICML 2017)
  • Xiaoxiao Guo, Tim Klinger, Clemens Rosenbaum, Joseph P. Bigus, Murray Campbell, B. Kawass, Kartik Talamadupula, and Gerald Tesauro. "Learning to query, reason and answer question on ambiguous texts." (ICLR 2017).
  • Ishan P. Durugkar, Clemens Rosenbaum, Stefan Dernbach, Sridhar Mahadevan. "Deep Reinforcement Learning With Macro-Actions" (arxiv, 2016).
  • Clemens Rosenbaum and Sridhar Mahadevan. "Boosting Gradient Algorithms for Multi-Agent Games" (LICMAS@NIPS 2015).


My preferred type of contact is via email at cgbr@cs.umass.edu.