Optimization of high order perceptrons

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Effective information sharing is essential for multi-agent systems to execute cooperative tasks successfully. Typically, agents within such systems are either stationary or possess unrestricted communication ranges. However, in more complex scenarios where ...

Depth matching well logs acquired from multiple logging passes in a single well has been a longstanding challenge for the industry. The existing approaches employed in commercial platforms are typically based on classical cross-correlation and covariance m ...

This contribution presents a new database to address current challenges in face recognition. It contains face video sequences of 75 individuals acquired either through a laptop webcam or when mimicking the front-facing camera of a smartphone. Sequences hav ...

The generalized command response (GCR) model represents intonation as a superposition of muscle responses to spike command signals. We have previously shown that the spikes can be predicted by a two-stage system, consisting of a recurrent neural network an ...

Several approaches have been proposed to assist humans in co-manipulation and teleoperation tasks given demonstrated trajectories. However, these approaches are not applicable when the demonstrations are suboptimal or when the generalization capabilities o ...

We propose a deep-learning approach for people detection on depth imagery. The approach is designed to be deployed as an autonomous appliance for identifying people attacks and intrusion in video surveillance scenarios. To this end, we propose a fully-conv ...

Network embedding automatically learns to encode a graph into multi-dimensional vectors. The embedded representation appears to outperform hand-crafted features in many downstream machine learning tasks. There are a plethora of network embedding approaches ...

The 6000 series Al alloys, which include a few percent of Mg and Si, are important in automotive and aviation industries because of their low weight, as compared to steels, and the fact their strength can be greatly improved through engineered precipitatio ...

In the last decade, i-vector and Joint Factor Analysis (JFA) approaches to speaker modeling have become ubiquitous in the area of automatic speaker recognition. Both of these techniques involve the computation of posterior probabilities, using either Gauss ...

Crows quickly learn arbitrary associations. As a neuronal correlate of this behavior, single neurons in the corvid endbrain area nidopallium caudolaterale (NCL) change their response properties during association learning. In crows performing a delayed ass ...

We introduce a novel Deep Network architecture that implements the full feature point handling pipeline, that is, detection, orientation estimation, and feature description. While previous works have successfully tackled each one of these problems individu ...

A wide variety of problems in machine learning, including exemplar clustering, document summarization, and sensor placement, can be cast as constrained submodular maximization problems. A lot of recent effort has been devoted to developing distributed algo ...

Neuronal firing, synaptic transmission, and its plasticity form the building blocks for processing and storage of information in the brain. It is unknown whether adult human synapses are more efficient in transferring information between neurons than roden ...

We present a comparative study of the performance of different basis functions for the nonparametric modeling of neural activity in response to natural stimuli. Based on naturalistic video sequences, a generative model of neural activity was created using ...

Modelling, dimensioning and performance analysis of optical backbone networks is the main concern of this thesis. Modelling consists in representing a network under a abstract form, simpler and easier to analyse, the model. Dimensioning is achieved when ne ...

Using phone posterior probabilities has been increasingly explored for improving automatic speech recognition (ASR) systems. In this paper, we propose two approaches for hierarchically enhancing these phone posteriors, by integrating long acoustic context, ...

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from single-gene single-protein experimental approach to studying the behaviour of a ...

With the rapid expansion in the use of computers for producing digitalized textual documents, the need of automatic systems for organizing and retrieving the information contained in large databases has become essential. In general, information retrieval s ...

The paper addresses the media-specific rate allocation problem in multipath networks. The streaming rate on each path is determined such that the end- to-end media distortion is minimized, when the receiving client aggregates packets received via multiple ...

This paper describes a new kind of genetic representation called analog genetic encoding (AGE). The representation is aimed at the evolutionary synthesis and reverse engineering of circuits and networks such as analog electronic circuits, neural networks, ...

Optimization of high order perceptrons

Chat with Graph Search

Dynamic Communication in Multi-Agent Reinforcement Learning via Information Bottleneck

A Machine-Learning Framework for Automating Well-Log Depth Matching

A Comprehensive Experimental and Reproducible Study on Selfie Biometrics in Multistream and Heterogeneous Settings

An End-to-End Networks to Synthetize Intonation using a Generalized Command Response Model

Learning Trajectory Distributions for Assisted Teleoperation and Path Planning

WatchNet: Efficient and Depth-based Network for People Detection in Video Surveillance Systems

A comparison of network embedding approaches

Neural network potential for Al-Mg-Si alloys

Template-matching for text-dependent speaker verification

Learning Recruits Neurons Representing Previously Established Associations in the Corvid Endbrain

LIFT: Learned Invariant Feature Transform

A New Framework for Distributed Submodular Maximization

High Bandwidth Synaptic Communication and Frequency Tracking in Human Neocortex

Spline- and Wavelet-based Models of Neural Activity in Response to Natural Visual Stimulation

Software Framework for Integrated Modelling and Dimensioning of Backbone Optical Networks

Enhanced Phone Posteriors for Improving Speech Recognition Systems

Implicit methods for modeling gene regulatory networks

Machine learning approaches to text representation using unlabeled data

Distributed Media Rate Allocation in Multipath Networks

Analog Genetic Encoding for the Evolution of Circuits and Networks