Search results for "Theoretical Computer Science"

A very brief history of soft computing: Fuzzy Sets, artificial Neural Networks and Evolutionary Computation

2013

This paper gives a brief presentation of history of Soft Computing considered as a mix of three scientific disciplines that arose in the mid of the 20th century: Fuzzy Sets and Systems, Neural Networks, and Evolutionary Computation. The paper shows the genesis and the historical development of the three disciplines and also their meeting in a coalition in the 1990s.

Using Tsetlin Machine to discover interpretable rules in natural language processing applications

2021

Tsetlin Machines (TM) use finite state machines for learning and propositional logic to represent patterns. The resulting pattern recognition approach captures information in the form of conjunctive clauses, thus facilitating human interpretation. In this work, we propose a TM-based approach to three common natural language processing (NLP) tasks, namely, sentiment analysis, semantic relation categorization and identifying entities in multi-turn dialogues. By performing frequent itemset mining on the TM-produced patterns, we show that we can obtain a global and a local interpretation of the learning, one that mimics existing rule-sets or lexicons. Further, we also establish that our TM base…

Increasing sample efficiency in deep reinforcement learning using generative environment modelling

2020

Hybrid architecture for shape reconstruction and object recognition

1998

The proposed architecture is aimed to recover 3-D- shape information from gray-level images of a scene; to build a geometric representation of the scene in terms of geometric primitives; and to reason about the scene. The novelty of the architecture is in fact the integration of different approaches: symbolic reasoning techniques typical of knowledge representation in artificial intelligence, algorithmic capabilities typical of artificial vision schemes, and analogue techniques typical of artificial neural networks. Experimental results obtained by means of an implemented version of the proposed architecture acting on real scene images are reported to illustrate the system capabilities.

Combining a context aware neural network with a denoising autoencoder for measuring string similarities

2020

Abstract Measuring similarities between strings is central for many established and fast-growing research areas, including information retrieval, biology, and natural-language processing. The traditional approach to string similarity measurements is to define a metric with respect to a word space that quantifies and sums up the differences between characters in two strings; surprisingly, these metrics have not evolved a great deal over the past few decades. Indeed, the majority of them are still based on making a simple comparison between character and character distributions without considering the words context. This paper proposes a string metric that encompasses similarities between str…

Asynchronous L1 control of delayed switched positive systems with mode-dependent average dwell time

2014

Abstract This paper investigates the stability and asynchronous L 1 control problems for a class of switched positive linear systems (SPLSs) with time-varying delays by using the mode-dependent average dwell time (MDADT) approach. By allowing the co-positive type Lyapunov–Krasovskii functional to increase during the running time of active subsystems, a new stability criterion for the underlying system with MDADT is first derived. Then, the obtained results are extended to study the issue of asynchronous L 1 control, where “asynchronous” means that the switching of the controllers has a lag with respect to that of system modes. Sufficient conditions are provided to guarantee that the resulti…

Auditory distance perception in an acoustic pipe

2008

In a study of auditory distance perception, we investigated the effects of exaggeration the acoustic cue of reverberation where the intensity of sound did not vary noticeably. The set of stimuli was obtained by moving a sound source inside a 10.2-m long pipe having a 0.3-m diameter. Twelve subjects were asked to listen to a speech sound while keeping their head inside the pipe and then to estimate the egocentric distance from the sound source using a magnitude production procedure. The procedure was repeated eighteen times using six different positions of the sound source. Results show that the point at which perceived distance equals physical distance is located approximately 3.5 m away fr…

Learning-Graph-Based Quantum Algorithm for k-distinctness

2012

We present a quantum algorithm solving the $k$-distinctness problem in $O(n^{1-2^{k-2}/(2^k-1)})$ queries with a bounded error. This improves the previous $O(n^{k/(k+1)})$-query algorithm by Ambainis. The construction uses a modified learning graph approach. Compared to the recent paper by Belovs and Lee arXiv:1108.3022, the algorithm doesn't require any prior information on the input, and the complexity analysis is much simpler. Additionally, we introduce an $O(\sqrt{n}\alpha^{1/6})$ algorithm for the graph collision problem where $\alpha$ is the independence number of the graph.

Probabilities of conditionals and previsions of iterated conditionals

2019

Abstract We analyze selected iterated conditionals in the framework of conditional random quantities. We point out that it is instructive to examine Lewis's triviality result, which shows the conditions a conditional must satisfy for its probability to be the conditional probability. In our approach, however, we avoid triviality because the import-export principle is invalid. We then analyze an example of reasoning under partial knowledge where, given a conditional if A then C as information, the probability of A should intuitively increase. We explain this intuition by making some implicit background information explicit. We consider several (generalized) iterated conditionals, which allow…

Taxonomic categorisation of motivic patterns

2009

The issue of pattern description in computational models for motivic analysis is closely related to the cognitive debate on categorisation, in which are traditionally opposed “well-defined” and “ill-defined” categorisations. The ill-defined conceptualisation has been considered as a suitable framework for the formalisation of musical categorisation as it takes into account motivic variations. It seems that computational models rely rather on well-defined categorisation, due to its better controllability. The computational model we previously presented (Lartillot & Toiviainen, 2007) strikes a balance by developing a new flexible framework allowing the taking into account of unrestricted…