
Task Affinity with Maximum Bipartite Matching in FewShot Learning
We propose an asymmetric affinity score for representing the complexity ...
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Towards Explainable Convolutional Features for Music Audio Modeling
Audio signals are often represented as spectrograms and treated as 2D im...
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Neural Architecture Search From Fréchet Task Distance
We formulate a Fréchettype asymmetric distance between tasks based on F...
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Neural Architecture Search From Task Similarity Measure
In this paper, we propose a neural architecture search framework based o...
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TaskAware Neural Architecture Search
The design of handcrafted neural networks requires a lot of time and res...
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An Interpretable Baseline for Time Series Classification Without Intensive Learning
Recent advances in time series classification have largely focused on me...
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Projected Latent Markov Chain Monte Carlo: Conditional Inference with Normalizing Flows
We introduce Projected Latent Markov Chain Monte Carlo (PLMCMC), a tech...
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Hyperparameter Optimization in Neural Networks via Structured Sparse Recovery
In this paper, we study two important problems in the automated design o...
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PerceptionDistortion Tradeoff with Restricted Boltzmann Machines
In this work, we introduce a new procedure for applying Restricted Boltz...
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OneShot Neural Architecture Search via Compressive Sensing
Neural architecture search (NAS), or automated design of neural network ...
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Learning Generative Models of Structured Signals from Their Superposition Using GANs with Application to Denoising and Demixing
Recently, Generative Adversarial Networks (GANs) have emerged as a popul...
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Fast LowRank Matrix Estimation without the Condition Number
In this paper, we study the general problem of optimizing a convex funct...
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Reconstruction from Periodic Nonlinearities, With Applications to HDR Imaging
We consider the problem of reconstructing signals and images from period...
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Demixing Structured Superposition Signals from Periodic and Aperiodic Nonlinear Observations
We consider the demixing problem of two (or more) structured highdimens...
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Fast Algorithms for Learning Latent Variables in Graphical Models
We study the problem of learning latent variables in Gaussian graphical ...
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Improved Algorithms for Matrix Recovery from RankOne Projections
We consider the problem of estimation of a lowrank matrix from a limite...
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Stable Recovery Of Sparse Vectors From Random Sinusoidal Feature Maps
Random sinusoidal features are a popular approach for speeding up kernel...
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Iterative Thresholding for Demixing Structured Superpositions in High Dimensions
We consider the demixing problem of two (or more) highdimensional vecto...
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Fast Algorithms for Demixing Sparse Signals from Nonlinear Observations
We study the problem of demixing a pair of sparse signals from noisy, no...
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Mohammadreza Soltani
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