I am a Postdoctaral Fellow at ETH
in the Learning
& Adaptive Systems Group
with Andreas Krause
I finished my PhD at the University
in 2012, under the supervision of Csaba
. I was a member of the Reinforcement Learning and
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My research interest is machine learning. My goal is to
better understand the theoretical limitations of machine
learning. Currently I am focusing on online learning. See my
The University of Alberta
nominated my thesis for the WAGS/UMI
Innovation in Technology Award. The winners will
be announced in March 2014 at the WAGS annual meeting.
Our paper with Navid Zolghadr, András
György, Csaba Szepesvári, and Russell
Greiner, titled Online Learning with Costly
Features and Labels, has been accepted for
poster presentation to NIPS2013.
with Gergely Neu, An efficient algorithm for learning
with semi-bandit feedback, has been accepted to
I won the 2013 Doctoral Dissertation Award
of the Canadian Artificial Intelligence Association!
My paper "A near-optimal algorithm for finite
partial-monitoring games against adversarial
opponents" has been accepted to COLT2013.
My PhD thesis is nominated for the AI
Doctoral Dissertation Award of the Canadian
Artificial Intelligence Association (CAIAC) by the Department
of Computing Science, University of Alberta
I gave a contributed talk at the NIPS2012 Workshop on
Information in Perception and Action, titled "The
value of information in online learning: A study of
partial monitoring problems"
Our paper with Csaba Szepesvári "Partial monitoring
with side information" has been accepted to ALT2012.
I defended my PhD thesis on the 22nd of June, 2012. My
thesis title is "The role of information in online
learning". I will upload the final version soon.
Our ICML2012 submission with Navid and Csaba "An
adaptive algorithm for finite stochastic partial
monitoring" has been accepted.
From mid-summer 2012, I will work as a postdoctoral
fellow with Andreas
Krause in the Learning &
Adaptive Systems Group at ETH Zürich.