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Annealing Knowledge Distillation
Significant memory and computational requirements of large deep neural n...
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Symbolically Solving Partial Differential Equations using Deep Learning
We describe a neural-based method for generating exact or approximate so...
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A Neuro-Symbolic Method for Solving Differential and Functional Equations
When neural networks are used to solve differential equations, they usua...
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Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and Survey
Stochastic Neighbor Embedding (SNE) is a manifold learning and dimension...
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Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey
Multidimensional Scaling (MDS) is one of the first fundamental manifold ...
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Segmentation Approach for Coreference Resolution Task
In coreference resolution, it is important to consider all members of a ...
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DeepNovoV2: Better de novo peptide sequencing with deep learning
We introduce DeepNovoV2, the state-of-the-art neural networks based mode...
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Deep Variational Sufficient Dimensionality Reduction
We consider the problem of sufficient dimensionality reduction (SDR), wh...
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SRP: Efficient class-aware embedding learning for large-scale data via supervised random projections
Supervised dimensionality reduction strategies have been of great intere...
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Text Classification based on Multiple Block Convolutional Highways
In the Text Classification areas of Sentiment Analysis, Subjectivity/Obj...
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A Berkeley View of Systems Challenges for AI
With the increasing commoditization of computer vision, speech recogniti...
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JADE: Joint Autoencoders for Dis-Entanglement
The problem of feature disentanglement has been explored in the literatu...
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Improving the Accuracy of Pre-trained Word Embeddings for Sentiment Analysis
Sentiment analysis is one of the well-known tasks and fast growing resea...
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Deep Structure for end-to-end inverse rendering
Inverse rendering in a 3D format denoted to recovering the 3D properties...
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Fast Spectral Clustering Using Autoencoders and Landmarks
In this paper, we introduce an algorithm for performing spectral cluster...
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Generative Mixture of Networks
A generative model based on training deep architectures is proposed. The...
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Semi-supervised Dictionary Learning Based on Hilbert-Schmidt Independence Criterion
In this paper, a novel semi-supervised dictionary learning and sparse re...
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On the Invariance of Dictionary Learning and Sparse Representation to Projecting Data to a Discriminative Space
In this paper, it is proved that dictionary learning and sparse represen...
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Supervised Dictionary Learning and Sparse Representation-A Review
Dictionary learning and sparse representation (DLSR) is a recent and suc...
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A Fast Greedy Algorithm for Generalized Column Subset Selection
This paper defines a generalized column subset selection problem which i...
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Supervised Texture Classification Using a Novel Compression-Based Similarity Measure
Supervised pixel-based texture classification is usually performed in th...
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Kernelized Supervised Dictionary Learning
In this paper, we propose supervised dictionary learning (SDL) by incorp...
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