AIEDU
2004
13 years 4 months ago
2004
Learning and reasoning from multiple documents requires students to employ the skills of sourcing (i.e., attending to and citing sources) and information integration (i.e., making ...
JSAC
2007
13 years 4 months ago
2007
Abstract— We consider multiuser scheduling with limited feedback of partial channel state information in MIMO broadcast channels. By using spatial multiplexing at the base statio...
JSAC
2007
13 years 4 months ago
2007
Abstract— We analyze the sum-rate performance of a multiantenna downlink system carrying more users than transmit antennas, with partial channel knowledge at the transmitter due ...
TROB
2008
13 years 4 months ago
2008
In this paper we show that for haptic rendering using position feedback, the structure of the feedback loop imposes a fundamental tradeoff between accurate rendering of virtual env...
TKDE
2008
13 years 4 months ago
2008
Relevance feedback (RF) is an iterative process, which refines the retrievals by utilizing the user's feedback on previously retrieved results. Traditional RF techniques solel...
TIT
2008
13 years 4 months ago
2008
Abstract--For output-symmetric discrete memoryless channels (DMCs) at even moderately high rates, fixed-block-length communication systems show no improvements in their error expon...
SIGIR
2008
ACM
13 years 4 months ago
2008
ACM
Negative relevance feedback is a special case of relevance feedback where we do not have any positive example; this often happens when the topic is difficult and the search result...
SIGIR
2008
ACM
13 years 4 months ago
2008
ACM
We examine the effect of incorporating gaze-based attention feedback from the user on personalizing the search process. Employing eye tracking data, we keep track of document part...
KES
2006
Springer
13 years 4 months ago
2006
Springer
Abstract. We have been developing a system AirTransNote, a computermediated learning system that employs digital pen to realize papercentric augmented classroom. Although the appro...
JMLR
2006
13 years 4 months ago
2006
We discuss the problem of learning to rank labels from a real valued feedback associated with each label. We cast the feedback as a preferences graph where the nodes of the graph ...