Most word embedding models typically represent each word using a single vector, which makes these models indiscriminative for ubiquitous homonymy and polysemy. In order to enhance...
Adaptive exploration uses active learning principles to improve the efficiency of autonomous robotic surveys. This work considers an important and understudied aspect of autonomo...
David Ray Thompson, David Wettergreen, Greydon T. ...
Graphical models provide a rich framework for summarizing the dependencies among variables. The graphical lasso approach attempts to learn the structure of a Gaussian graphical mo...
Maxim Grechkin, Maryam Fazel, Daniela M. Witten, S...
Hippocampal place cells and entorhinal grid cells have been hypothesized to be able to form map-like spatial representation of the environment, namely cognitive map. In most prior...
Miaolong Yuan, Bo Tian, Vui Ann Shim, Huajin Tang,...
Computing prices in core-selecting combinatorial auctions is a computationally hard problem. Auctions with many bids can only be solved using a recently proposed core constraint g...
Topic models remain a black box both for modelers and for end users in many respects. From the modelers’ perspective, many decisions must be made which lack clear rationales and...
Monte-Carlo Tree Search, especially UCT and its POMDP version POMCP, have demonstrated excellent performance on many problems. However, to efficiently scale to large domains one ...
Faced with the problem of characterizing systematic changes in multivariate time series in an unsupervised manner, we derive and test two methods of regularizing hidden Markov mod...
George D. Montanez, Saeed Amizadeh, Nikolay Laptev
With the extensive application of submodularity, its generalizations are constantly being proposed. However, most of them are tailored for special problems. In this paper, we focu...
A key challenge in the design of multi-sensor systems is the efficient allocation of scarce resources such as bandwidth, CPU cycles, and energy, leading to the dynamic sensor sel...