Many problems in artificial intelligence require adaptively making a sequence of decisions
with uncertain outcomes under partial observability. Solving such stochastic optimization …

We tackle the fundamental problem of Bayesian active learning with noise, where we need
to adaptively select from a number of expensive tests in order to identify an unknown …

Correct identification of diatom taxa is indispensable for diatom-based water quality studies,
as well as for biotechnological applications. Biological applications of taxonomy include the …

In this paper, we propose minimum-effort driven navigational techniques for enterprise
database systems based on the faceted search paradigm. Our proposed techniques …

In contrast to classic geometric motion planning, informative path planning (IPP) seeks a
path for a robot to sense the world and gain information. In adaptive IPP, the robot chooses …

Abstract A $ k $-decision tree $ t $(or $ k $-tree) is a recursive partition of a matrix (2D-
signal) into $ k\geq 1$ block matrices (axis-parallel rectangles, leaves) where each …

Credential stuffing attacks use stolen passwords to log into victim accounts. To defend
against these attacks, recently deployed compromised credential checking (C3) services …

Monitoring human activities using wearable sensor nodes has the potential to enable many
useful applications for everyday situations. Limited computation, battery lifetime and …

We consider the problem of constructing optimal decision trees: given a collection of tests
that can disambiguate between a set of m possible diseases, each test having a cost, and …

Interactive program synthesis aims to solve the ambiguity in specifications, and selecting the
proper question to minimize the rounds of interactions is critical to the performance of …