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Meta-Learning Bidirectional Update Rules
In this paper, we introduce a new type of generalized neural network whe...
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Transfer Learning for Piano Sustain-Pedal Detection
Detecting piano pedalling techniques in polyphonic music remains a chall...
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SpotPatch: Parameter-Efficient Transfer Learning for Mobile Object Detection
Deep learning based object detectors are commonly deployed on mobile dev...
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Large-Scale Generative Data-Free Distillation
Knowledge distillation is one of the most popular and effective techniqu...
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Image segmentation via Cellular Automata
In this paper, we propose a new approach for building cellular automata ...
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Structured Multi-Hashing for Model Compression
Despite the success of deep neural networks (DNNs), state-of-the-art mod...
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Non-discriminative data or weak model? On the relative importance of data and model resolution
We explore the question of how the resolution of the input image ("input...
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Information-Bottleneck Approach to Salient Region Discovery
We propose a new method for learning image attention masks in a semi-sup...
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Adversarial Attacks in Sound Event Classification
Adversarial attacks refer to a set of methods that perturb the input to ...
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Efficient On-line Computation of Visibility Graphs
A visibility algorithm maps time series into complex networks following ...
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Searching for MobileNetV3
We present the next generation of MobileNets based on a combination of c...
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Visibility graphs for robust harmonic similarity measures between audio spectra
Graph theory is emerging as a new source of tools for time series analys...
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K For The Price Of 1: Parameter Efficient Multi-task And Transfer Learning
We introduce a novel method that enables parameter-efficient transfer an...
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Does k Matter? k-NN Hubness Analysis for Kernel Additive Modelling Vocal Separation
Kernel Additive Modelling (KAM) is a framework for source separation aim...
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Similarity measures for vocal-based drum sample retrieval using deep convolutional auto-encoders
The expressive nature of the voice provides a powerful medium for commun...
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Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation
In this paper we describe a new mobile architecture, MobileNetV2, that i...
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Inverted Residuals and Linear Bottlenecks: Mobile Networks forClassification, Detection and Segmentation
In this paper we describe a new mobile architecture, MobileNetV2, that i...
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CycleGAN: a Master of Steganography
CycleGAN is one of the latest successful approaches to learn a correspon...
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A Tutorial on Deep Learning for Music Information Retrieval
Following their success in Computer Vision and other areas, deep learnin...
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A Comparison on Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging
Deep neural networks (DNN) have been successfully applied for music clas...
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The Effects of Noisy Labels on Deep Convolutional Neural Networks for Music Tagging
Deep neural networks (DNN) have been successfully applied to music class...
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Transfer learning for music classification and regression tasks
In this paper, we present a transfer learning approach for music classif...
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The Power of Sparsity in Convolutional Neural Networks
Deep convolutional networks are well-known for their high computational ...
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Convolutional Recurrent Neural Networks for Music Classification
We introduce a convolutional recurrent neural network (CRNN) for music t...
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Towards Music Captioning: Generating Music Playlist Descriptions
Descriptions are often provided along with recommendations to help users...
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Explaining Deep Convolutional Neural Networks on Music Classification
Deep convolutional neural networks (CNNs) have been actively adopted in ...
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Inverting face embeddings with convolutional neural networks
Deep neural networks have dramatically advanced the state of the art for...
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Towards Playlist Generation Algorithms Using RNNs Trained on Within-Track Transitions
We introduce a novel playlist generation algorithm that focuses on the q...
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