research
∙
03/09/2022
Monitoring Time Series With Missing Values: a Deep Probabilistic Approach
Systems are commonly monitored for health and security through collectio...
share
research
∙
08/09/2021
Bob and Alice Go to a Bar: Reasoning About Future With Probabilistic Programs
Agent preferences should be specified stochastically rather than determi...
research
∙
05/08/2021
How To Train Your Program
We present a Bayesian approach to machine learning with probabilistic pr...
research
∙
10/01/2020
Bayesian Policy Search for Stochastic Domains
AI planning can be cast as inference in probabilistic models, and probab...
research
∙
10/01/2020
Probabilistic Programs with Stochastic Conditioning
We tackle the problem of conditioning probabilistic programs on distribu...
research
∙
03/02/2020
Stochastically Differentiable Probabilistic Programs
Probabilistic programs with mixed support (both continuous and discrete ...
research
∙
01/08/2020
Stochastic probabilistic programs
We introduce the notion of a stochastic probabilistic program and presen...
research
∙
12/05/2019
Warped Input Gaussian Processes for Time Series Forecasting
We introduce a Gaussian process-based model for handling of non-stationa...
research
∙
06/20/2019
Deployable probabilistic programming
We propose design guidelines for a probabilistic programming facility su...
research
∙
05/05/2018
Population Anomaly Detection through Deep Gaussianization
We introduce an algorithmic method for population anomaly detection base...
research
∙
09/24/2017
Intrusions in Marked Renewal Processes
We present a probabilistic model of an intrusion in a marked renewal pro...
research
∙
09/11/2017
A Planning Approach to Monitoring Behavior of Computer Programs
We describe a novel approach to monitoring high level behaviors using co...
research
∙
07/12/2017
Process Monitoring on Sequences of System Call Count Vectors
We introduce a methodology for efficient monitoring of processes running...
research
∙
06/20/2017
Session Analysis using Plan Recognition
This paper presents preliminary results of our work with a major financi...
research
∙
04/26/2015
Maximum a Posteriori Estimation by Search in Probabilistic Programs
We introduce an approximate search algorithm for fast maximum a posterio...
research
∙
02/25/2015
Path Finding under Uncertainty through Probabilistic Inference
We introduce a new approach to solving path-finding problems under uncer...
research
∙
01/22/2015
Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs
We introduce an adaptive output-sensitive Metropolis-Hastings algorithm ...
research
∙
11/24/2014
Rational Deployment of Multiple Heuristics in IDA*
Recent advances in metareasoning for search has shown its usefulness in ...
research
∙
10/23/2014
Justifying and Improving Meta-Agent Conflict-Based Search
The Meta-Agent Conflict-Based Search (MA-CBS) is a recently proposed alg...
research
∙
08/09/2014
Selecting Computations: Theory and Applications
Sequential decision problems are often approximately solvable by simulat...
research
∙
05/22/2013
Towards Rational Deployment of Multiple Heuristics in A*
The obvious way to use several admissible heuristics in A* is to take th...
research
∙
07/24/2012
VOI-aware MCTS
UCT, a state-of-the art algorithm for Monte Carlo tree search (MCTS) in ...
research
∙
07/23/2012
MCTS Based on Simple Regret
UCT, a state-of-the art algorithm for Monte Carlo tree search (MCTS) in ...
research
∙
08/18/2011
Doing Better Than UCT: Rational Monte Carlo Sampling in Trees
UCT, a state-of-the art algorithm for Monte Carlo tree sampling (MCTS), ...
research
∙
04/11/2011
Rational Deployment of CSP Heuristics
Heuristics are crucial tools in decreasing search effort in varied field...
research
∙
03/27/2010
Rational Value of Information Estimation for Measurement Selection
Computing value of information (VOI) is a crucial task in various aspect...
research
∙
06/17/2009