Publications related to Conditional probability table

Distributionally Robust Optimization with Polynomial Densities: Theory, Models and Algorithms

In distributionally robust optimization the probability distribution of the uncertain problem parameters is itself uncertain, and a fictitious adversary, e.g., nature, chooses the worst distribution from within a known ambiguity set. A common shortcoming o ...

2020

On quantifying the quality of acoustic models in hybrid DNN-HMM ASR

Hervé Bourlard, Afsaneh Asaei, Pranay Dighe

We propose an information theoretic framework for quantitative assessment of acoustic models used in hidden Markov model (HMM) based automatic speech recognition (ASR). The HMM backend expects that (i) the acoustic model yields accurate state conditional e ...

ELSEVIER2020

Safely Managed Hygiene: A Risk-Based Assessment of Handwashing Water Quality

Matthew Eric Verbyla, Timothy R. Julian

Sustainable Development Goal (SDG) Indicator 6.2.1 requires household handwashing facilities to have soap and water, but there are no guidelines for handwashing water quality. In contrast, drinking water quality guidelines are defined: water must be "free ...

2019

Multi-Modal Mean-Fields via Cardinality-Based Clamping

Pascal Fua, François Fleuret

Mean Field inference is central to statistical physics. It has attracted much interest in the Computer Vision community to efficiently solve problems expressible in terms of large Conditional Random Fields. However, since it models the posterior probabilit ...

Ieee2017

High Resolution Air Pollution Maps in Urban Environments Using Mobile Sensor Networks

Alcherio Martinoli, Ali Marjovi, Adrian Arfire

We propose three modeling methods using a mobile sensor network to generate high spatio-temporal resolution air pollution maps for urban environments. In our deployment in Lausanne (Switzerland), dedicated sensing nodes are anchored to the public buses and ...

IEEE2015

Pattern-wise trust assessment of sensor data

Karl Aberer, Mehdi Riahi, Robert Gwadera

One of the most important tasks of a sensor network (SN) is to detect occurrences of interesting events in the monitored environment. However, data measured by SN is often affected by errors. We investigate the problem of assessing trustworthiness (trust) ...

2014

A bottom-up stochastic model to predict building occupants' time-dependent activities

Jean-Louis Scartezzini, Darren Robinson, Frédéric Haldi, Urs Wilke

A bottom-up modelling approach together with a set of calibration methodologies is presented to predict residential building occupants' time-dependent activities, for use in dynamic building simulations. The stochastic model to predict activity chains is c ...

Elsevier2013

Conditional probabilities in the excursion set theory: generic barriers and non-Gaussian initial conditions

Andrea De Simone, Michele Maggiore

The excursion set theory, where density perturbations evolve stochastically with the smoothing scale, provides a method for computing the dark matter halo mass function. The computation of the mass function is mapped into the so-called first-passage time p ...

Blackwell Publishing Ltd, Oxford2011

Display probability modulates attentional capture by onset distractors

Michael Herzog, Bilge Sayim

Attention can be stimulus-driven and bottom-up or goal-driven and top-down. Bottom-up attention and, particularly, attentional capture are often thought to be strongly automatic, i.e., not modulable. For example, in visual search, it has been shown that sa ...

Association for Research in Vision and Ophthalmology2010

Modulation of Attentional Capture by Display Probabilities in Visual Search

Michael Herzog, Bilge Sayim

Attentional capture is often thought to be automatic and not modulable. For example, visual search experiments showed that salient distractor singletons strongly capture attention even when they had to be ignored by the observers. Recently, however, it was ...

2009

Closed-form solutions to stochastic switching problems

Erwan Morellec

This paper studies the price of an asset depending on both a fundamental and possible interventions of an authority. Using the martingale approach in continuous time, we provide closed-form solutions to switching problems involving irreversible, state depe ...

2008

Principled Detection-by-Classification from Multiple Views

Pascal Fua, François Fleuret, Jérôme Berclaz

Machine-learning based classification techniques have been shown to be effective at detecting objects in complex scenes. However, the final results are often obtained from the alarms produced by the classifiers through a post-processing which typically rel ...

2008