Publications related to Boltzmann machine

Chemical machine learning with kernels: The impact of loss functions

Volkan Cevher, Quoc Tran Dinh, Sandip De, Junhong Lin

Machine learning promises to accelerate materials discovery by allowing computational efficient property predictions from a small number of reference calculations. As a result, the literature has spent a considerable effort in designing representations tha ...

2019

Cortical reliability amid noise and chaos

Henry Markram, Eilif Benjamin Muller, Michael Reimann, James Gonzalo King, Max Christian Nolte

Typical responses of cortical neurons to identical sensory stimuli appear highly variable. It has thus been proposed that the cortex primarily uses a rate code. However, other studies have argued for spike-time coding under certain conditions. The potentia ...

2019

Cross-lingual Adaptation of a CTC-based multilingual Acoustic Model

Hervé Bourlard, Philip Neil Garner, Sibo Tong

Multilingual models for Automatic Speech Recognition (ASR) are attractive as they have been shown to benefit from more training data, and better lend themselves to adaptation to under-resourced languages. However, initialisation from monolingual context-de ...

ELSEVIER SCIENCE BV2018

Robust and Discriminative Speaker Embedding via Intra-Class Distance Variance Regularization

Jean-Marc Odobez

Learning a good speaker embedding is critical for many speech processing tasks, including recognition, verification, and diarization. To this end, we propose a complementary optimizing goal called intra-class loss to improve deep speaker embed dings learne ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Chemical machine learning with kernels: The key impact of loss functions

Volkan Cevher, Sandip De, Junhong Lin, Van Quang Nguyen

Machine learning promises to accelerate materials discovery by allowing computational efficient property predictions from a small number of reference calculations. As a result, the literature spent a considerable effort in designing representations that ca ...

2018

Subspace Regularized Dynamic Time Warping for Spoken Query Detection

Hervé Bourlard, Afsaneh Asaei, Dhananjay Ram

Deep neural network posterior probabilities are the best features for query detection in speech archives. Dynamic time warping (DTW) is the state-of-the-art solution for this task. Posterior features live in low-dimensional subspaces whereas, the current D ...

2017

Error Tolerance Analysis of Deep Learning Hardware Using a Restricted Boltzmann Machine Toward Low-Power Memory Implementation

Alexandre Schmid, Takao Marukame, Kodai Ueyoshi

Remarkable hardware robustness of deep learning (DL) is revealed by error injection analyses performed using a custom hardware model implementing parallelized restricted Boltzmann machines (RBMs). RBMs in deep belief networks demonstrate robustness against ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Cortical Dynamics in Presence of Assemblies of Densely Connected Weight-Hub Neurons

Wulfram Gerstner, Moritz Deger, Hesam Setareh

Experimental measurements of pairwise connection probability of pyramidal neurons together with the distribution of synaptic weights have been used to construct randomly connected model networks. However, several experimental studies suggest that both wiri ...

Frontiers Research Foundation2017

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Boltzmann machine

Chemical machine learning with kernels: The impact of loss functions

Cortical reliability amid noise and chaos

Cross-lingual Adaptation of a CTC-based multilingual Acoustic Model

Robust and Discriminative Speaker Embedding via Intra-Class Distance Variance Regularization

Theory and Algorithms for Hypothesis Transfer Learning

Chemical machine learning with kernels: The key impact of loss functions

Subspace Regularized Dynamic Time Warping for Spoken Query Detection

Error Tolerance Analysis of Deep Learning Hardware Using a Restricted Boltzmann Machine Toward Low-Power Memory Implementation

Cortical Dynamics in Presence of Assemblies of Densely Connected Weight-Hub Neurons

Machine Vision algorithms on cadaster plans

Graph Chatbot

Chat with Graph Search

Chemical machine learning with kernels: The impact of loss functions

Cortical reliability amid noise and chaos

Cross-lingual Adaptation of a CTC-based multilingual Acoustic Model

Robust and Discriminative Speaker Embedding via Intra-Class Distance Variance Regularization

Theory and Algorithms for Hypothesis Transfer Learning

Chemical machine learning with kernels: The key impact of loss functions

Subspace Regularized Dynamic Time Warping for Spoken Query Detection

Error Tolerance Analysis of Deep Learning Hardware Using a Restricted Boltzmann Machine Toward Low-Power Memory Implementation

Cortical Dynamics in Presence of Assemblies of Densely Connected Weight-Hub Neurons

Machine Vision algorithms on cadaster plans