
Browse All Reviews > Mathematics Of Computing (G) > Probability And Statistics (G.3) > Markov Processes (G.3...)









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Reviews about "Markov Processes (G.3...)":

Date Reviewed 

Reasoning with probabilistic and deterministic graphical models: exact algorithms (2nd ed.) Dechter R., Morgan&Claypool Publishers, San Rafael, CA, 2019. 200 pp. Type: Book (9781681734903) Many problems related to learning and reasoning can make use of graphical models where a knowledge structure is compactly encoded into a graph. When dependencies (or independencies) among the variables of concern are effectively captured in graphi...

May 4 2021 

Interactive recommendation with userspecific deep reinforcement learning Lei Y., Li W. ACM Transactions on Knowledge Discovery from Data 13(6): 115, 2019. Type: Article Recommender systems are widely used, especially by online applications with a view to enhancing user experience. In most conventional systems, past history of a user’s implicit online behavior is used to derive a new recommendation. By enabl...

Mar 2 2020 

Unifying logical and statistical AI with Markov logic Domingos P., Lowd D. Communications of the ACM 62(7): 7483, 2019. Type: Article A Markov logic network (MLN) is a probabilistic logic that endows the firstorder logic with a degree of uncertainty by applying Markov networks. It represents an active area of research, introduced in the early 2000s by the very authors of the pr...

Sep 20 2019 

Answer set programming for nonstationary Markov decision processes Ferreira L., Bianchi R., Santos P., Lopez de Mantaras R. Applied Intelligence 47(4): 9931007, 2017. Type: Article Problem solving with computers often involves the exploration of paths from an initial state to a goal state. In addition to the size of this search space, there are many factors complicating this approach, especially in realistic environments. In...

Mar 13 2018 

Analyzing sentiments in one go: a supervised joint topic modeling approach Hai Z., Cong G., Chang K., Cheng P., Miao C. IEEE Transactions on Knowledge and Data Engineering 29(6): 11721185, 2017. Type: Article The socalled “crowd wisdom” phenomenon took on a whole new dimension with the advent of the web and the emergence of myriads of online product reviews written by both happy and (more often than not) angry customers. A thorough underst...

Jan 17 2018 

Markov chains and Markov decision processes in Isabelle/HOL Hölzl J. Journal of Automated Reasoning 59(3): 345387, 2017. Type: Article The intermingling of rather different domains can, at times, produce rather interesting results. Here the author explores the intersection of probability theory (in the guise of Markov chains and Markov decision processes) and formal proof (throug...

Jan 11 2018 

MixedTrails: Bayesian hypothesis comparison on heterogeneous sequential data Becker M., Lemmerich F., Singer P., Strohmaier M., Hotho A. Data Mining and Knowledge Discovery 31(5): 13591390, 2017. Type: Article This wellwritten paper includes adequate definitions to enable a layperson to understand the principles (generative processes of heterogeneous sequence data of human movement in a city) examined in its simulated experimental study. It uses approp...

Dec 7 2017 

Temporal probabilistic measure for link prediction in collaborative networks Jaya Lakshmi T., Durga Bhavani S. Applied Intelligence 47(1): 8395, 2017. Type: Article Research on social networks is a fashionable field, along with forecasting the behaviors of entities that are represented as nodes in a graph describing the relationship between entities. The authors investigate opportunities for the improvement o...

Sep 12 2017 

Brain tumor segmentation from multimodal magnetic resonance images via sparse representation Li Y., Jia F., Qin J. Artificial Intelligence in Medicine 73113, 2016. Type: Article The segmentation of brain tumors in magnetic resonance imaging (MRI) is clearly not only an important image processing task, but one in which the achievement of high accuracy can be lifechanging for many. Although MRIs are performed in a number o...

Jul 13 2017 

Markov chain aggregation for agentbased models Banisch S., Springer International Publishing, New York, NY, 2015. 195 pp. Type: Book (9783319248752) Most techniques for modeling dynamic systems fall into one of two categories. Equationbased models such as system dynamics and other differential equation formalisms seek a closedform expression for the overall dynamics, but typically characteri...

Jul 12 2017 





