Epistemology
Epistemology is the study of the nature of knowledge, justification, and the rationality of belief. Much debate in epistemology centers on four areas:
(1) the philosophical analysis of the nature of knowledge and how it relates to such concepts as truth, belief, and justification,
(2) various problems of skepticism,
(3) the sources and scope of knowledge and justified belief, and
(4) the criteria for knowledge and justification.
Epistemology addresses such questions as: ‘What makes justified beliefs justified?’, ‘What does it mean to say that we know something?’, and fundamentally ‘How do we know that we know?’. …

Torch
Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. A summary of core features:
· a powerful N-dimensional array
· lots of routines for indexing, slicing, transposing, …
· amazing interface to C, via LuaJIT
· linear algebra routines
· neural network, and energy-based models
· numeric optimization routines
· Fast and efficient GPU support
· Embeddable, with ports to iOS, Android and FPGA backends
https://…/torch7 …

Applied Singular Spectrum Analysis (ASSA)
Functions to model and decompose time series into principal components using singular spectrum analysis (de Carvalho and Rua (2017) <doi:10.1016/j.ijforecast.2015.09.004>; de Carvalho et al (2012) <doi:10.1016/j.econlet.2011.09.007>). …

Entity-Relationship Dependence Model (ERDM)
Entity-Relationship (E-R) Search is a complex case of Entity Search where the goal is to search for multiple unknown entities and relationships connecting them. We assume that a E-R query can be decomposed as a sequence of sub-queries each containing keywords related to a specific entity or relationship. We adopt a probabilistic formulation of the E-R search problem. When creating specific representations for entities (e.g. context terms) and for pairs of entities (i.e. relationships) it is possible to create a graph of probabilistic dependencies between sub-queries and entity plus relationship representations. To the best of our knowledge this represents the first probabilistic model of E-R search. We propose and develop a novel supervised Early Fusion-based model for E-R search, the Entity-Relationship Dependence Model (ERDM). It uses Markov Random Field to model term dependencies of E-R sub-queries and entity/relationship documents. We performed experiments with more than 800M entities and relationships extractions from ClueWeb-09-B with FACC1 entity linking. We obtained promising results using 3 different query collections comprising 469 E-R queries, with results showing that it is possible to perform E-R search without using fix and pre-defined entity and relationship types, enabling a wide range of queries to be addressed. …