Results 101 to 110 of about 8,159 (239)
Gait recognition using HMMs and dual discriminative observations for sub-dynamics analysis [PDF]
, 2013 This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2013 IEEE. Personal use of this material is permitted.
Huang, X, Boulgouris, NV
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Conversational AI Agents: The Effect of Process and Outcome Variation on Anthropomorphism and Trust
Information Systems Journal, Volume 36, Issue 4, Page 597-623, July 2026.ABSTRACT Organisations increasingly deploy conversational AI agents (CAs) in agentic roles where behavioural variations are inevitable. Prior work often conflates two distinct forms of variation: outcome variation (where success fluctuates) and process variation (where the path to completion varies).
Kambiz Saffarizadeh, Mark Keil
wiley +1 more source
Properties of the Statistical Complexity Functional and Partially Deterministic HMMs
Entropy, 2009 Statistical complexity is a measure of complexity of discrete-time stationary stochastic processes, which has many applications. We investigate its more abstract properties as a non-linear function of the space of processes and show its close relation to
Wolfgang Löhr
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Automation and Augmentation in Theological Perspective
Modern Theology, Volume 42, Issue 3, Page 612-628, July 2026.Abstract AI enables forms of automation that threaten unemployment and deskilling, eliminating important opportunities for the development of virtue. The concomitant loss of virtue and meaningful employment makes it a theological problem from the perspective of Catholic social teaching and theological anthropology.
Paul Scherz
wiley +1 more source
, 2018 : "A semi-continuous hidden Markov model based on multiple vector quantization codebooks is used here for large-vocabulary speaker-independent continuous speech recognition.
Kai-Fu Lee (5411312) +2 more
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Hidden Markov and Hidden Semi-Markov models on Financial Timeseries
, 2020 Masteroppgave i statistikk STAT399 MAMN ...
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A Survey for Deep Reinforcement Learning Based Network Intrusion Detection
Applied AI Letters, Volume 7, Issue 2, June 2026.This paper surveys deep reinforcement learning (DRL) for network intrusion detection, evaluating model efficiency, minority attack detection, and dataset imbalance. Findings show DRL achieves state‐of‐the‐art results on public datasets, sometimes surpassing traditional deep learning.
Wanrong Yang +3 more
wiley +1 more source
multi-state non-homogeneous semi-markov model of daily activity type, timing and duration sequence [PDF]
Understanding travelers' daily travel-activity pattern formation is an important issue for activity-based travel demand analysis. The activity pattern formation concerns not only complex interrelations between household members and individual's socio ...
Charles Raux +3 more
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Computational methods for discrete hidden semi-markov chains
We propose a computational approach for implementing discrete hidden semi-Markov chains. A discrete hidden semi-Markov chain is composed of a non-observable or hidden process which is a finite semi-Markov chain and a discrete observable process.
Guédon, Yann
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A hidden semi-Markov model for segmenting environmental toroidal data [PDF]
, 2020 Toroidal time series are temporal sequences of bivariate angular observations that often arise in environmental and ecological studies. A hidden semi- Markov model is proposed for segmenting these data according to a finite number of latent classes ...
Antonello Maruotti, Francesco Lagona
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