Search results for "Machine learning."
showing 10 items of 1455 documents
Learned Sorted Table Search and Static Indexes in Small-Space Data Models
2023
Machine-learning techniques, properly combined with data structures, have resulted in Learned Static Indexes, innovative and powerful tools that speed up Binary Searches with the use of additional space with respect to the table being searched into. Such space is devoted to the machine-learning models. Although in their infancy, these are methodologically and practically important, due to the pervasiveness of Sorted Table Search procedures. In modern applications, model space is a key factor, and a major open question concerning this area is to assess to what extent one can enjoy the speeding up of Binary Searches achieved by Learned Indexes while using constant or nearly constant-space mod…
Some Experiments in Supervised Pattern Recognition with Incomplete Training Samples
2002
This paper presents some ideas about automatic procedures to implement a system with the capability of detecting patterns arising from classes not represented in the training sample. The procedure aims at incorporating automatically to the training sample the necessary information about the new class for correctly recognizing patterns from this class in future classification tasks. The Nearest Neighbor rule is employed as the central classifier and several techniques are added to cope with the peril of incorporating noisy data to the training sample. Experimental results with real data confirm the benefits of the proposed procedure.
Towards Efficient Teacher Assisted Assignment Marking Using Ranking Metrics
2017
This paper describes a tool with supporting methodology for efficient teacher assisted marking of open assignments based on student answer ranking metrics. It includes a methodology for how to design tasks for markability. This improves marking efficienty and reduces cognitive strain for the teacher during marking, and also allows for easily giving feedback to students on common pitfalls and misconceptions to improve both the learning outcome for the students as well as the teacher’s productivity by reducing the time needed for marking open assignments. An advantage with the method is that it is language agnostic as well as generally being agnostic to the discipline of the course being asse…
Ontology-Guided Approach to Feature-Based Opinion Mining
2011
The boom of the Social Web has had a tremendous impact on a number of different research topics. In particular, the possibility to extract various kinds of added-value, informational elements from users' opinions has attracted researchers from the information retrieval and computational linguistics fields. However, current approaches to socalled opinion mining suffer from a series of drawbacks. In this paper we propose an innovative methodology for opinion mining that brings together traditional natural language processing techniques with sentimental analysis processes and Semantic Web technologies. The main goals of this methodology is to improve feature-based opinion mining by employing o…
Learning high-level manipulative tasks through imitation
2006
This paper presents ConSCIS, Conceptual Space based Cognitive Imitation System, which tightly links low-level data processing with knowledge representation in the context of robot imitation. Our focus is on the program-level imitation: we are interested in the final effects of actions on objects, and not on the particular kinematic or dynamic properties of the motion. The same architecture is used both to analyze and represent the task to be imitated, and to perform the imitation by generalizing in novel and different circumstances. The implemented experimental scenario is a two dimensional world populated with various objects in which observation/imitation takes place. To validate our appr…
Information Decomposition in Multivariate Systems: Definitions, Implementation and Application to Cardiovascular Networks
2016
The continuously growing framework of information dynamics encompasses a set of tools, rooted in information theory and statistical physics, which allow to quantify different aspects of the statistical structure of multivariate processes reflecting the temporal dynamics of complex networks. Building on the most recent developments in this field, this work designs a complete approach to dissect the information carried by the target of a network of multiple interacting systems into the new information produced by the system, the information stored in the system, and the information transferred to it from the other systems; information storage and transfer are then further decomposed into amou…
The human-computer connection: An overview of brain-computer interfaces
2018
This article introduces the field of brain-computer interfaces (BCI), which allows the control of devices without the generation of any active motor output but directly from the decoding of the user’s brain signals. Here we review the current state of the art in the BCI field, discussing the main components of such an interface and illustrating ongoing research questions and prototypes for controlling a large variety of devices, from virtual keyboards for communication to robotics systems to replace lost motor functions and even clinical interventions for motor rehabilitation after a stroke. The article concludes with some insights into the future of BCI.
Machine Learning-Based View Synthesis in Fourier Lightfield Microscopy
2022
Current interest in Fourier lightfield microscopy is increasing, due to its ability to acquire 3D images of thick dynamic samples. This technique is based on simultaneously capturing, in a single shot, and with a monocular setup, a number of orthographic perspective views of 3D microscopic samples. An essential feature of Fourier lightfield microscopy is that the number of acquired views is low, due to the trade-off relationship existing between the number of views and their corresponding lateral resolution. Therefore, it is important to have a tool for the generation of a high number of synthesized view images, without compromising their lateral resolution. In this context we investigate h…
Neural networks as effective techniques in clinical management of patients: some case studies
2004
In this paper, we present four examples of effective implementation of neural systems in the daily clinical practice. There are two main goals in this work; the first one is to show that neural networks are especially well-suited tools for solving different kind of medical/pharmaceutical problems, given the complex input output relationships and the few a priori knowledge about data distribution and variable relations. The second goal is to develop specific software applications, which enclose complex mathematical models, to clinicians; thus, the use of such models as decision support systems is facilitated. Four important pharmaceutical problems are considered in this study: identificatio…
Architectural improvements and FPGA implementation of a multimodel neuroprocessor
2003
Since neural networks (NNs) require an enormous amount of learning time, various kinds of dedicated parallel computers have been developed. In the paper a 2-D systolic array (SA) of dedicated processing elements (PEs) also called systolic cells (SCs) is presented as the heart of a multimodel neural-network accelerator. The instruction set of the SA allows the implementation of several neural algorithms, including error back propagation and a self organizing feature map algorithm. Several special architectural facilities are presented in the paper in order to improve the 2-D SA performance. A swapping mechanism of the weight matrix allows the implementation of NNs larger than 2-D SA. A systo…