Vahid Tarokh

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Duke University ∙ Harvard University

Rhodes Family Professor of Electrical and Computer Engineering. Professor of Electrical and Computer Engineering. Professor of Computer Science (Secondary). Professor of Mathematics (Secondary).

Semi-Empirical Objective Functions for MCMC Proposal Optimization

We introduce and demonstrate a semi-empirical procedure for determining ...
06/03/2021 ∙ by Chris Cannella, et al. ∙ 0 ∙ share

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SemiFL: Communication Efficient Semi-Supervised Federated Learning with Unlabeled Clients

Federated Learning allows training machine learning models by using the ...
06/02/2021 ∙ by Enmao Diao, et al. ∙ 0 ∙ share

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Gradient Assisted Learning

In distributed settings, collaborations between different entities, such...
06/02/2021 ∙ by Enmao Diao, et al. ∙ 0 ∙ share

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Towards Explainable Convolutional Features for Music Audio Modeling

Audio signals are often represented as spectrograms and treated as 2D im...
05/31/2021 ∙ by Anna K. Yanchenko, et al. ∙ 32 ∙ share

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Neural Architecture Search From Fréchet Task Distance

We formulate a Fréchet-type asymmetric distance between tasks based on F...
03/23/2021 ∙ by Cat P. Le, et al. ∙ 0 ∙ share

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Talaria: A Framework for Simulation of Permissioned Blockchains for Logistics and Beyond

In this paper, we present Talaria, a novel permissioned blockchain simul...
03/03/2021 ∙ by Jiali Xing, et al. ∙ 0 ∙ share

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Neural Architecture Search From Task Similarity Measure

In this paper, we propose a neural architecture search framework based o...
02/27/2021 ∙ by Cat P. Le, et al. ∙ 0 ∙ share

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Generative Archimedean Copulas

We propose a new generative modeling technique for learning multidimensi...
02/22/2021 ∙ by Yuting Ng, et al. ∙ 7 ∙ share

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Deep Extreme Value Copulas for Estimation and Sampling

We propose a new method for modeling the distribution function of high d...
02/17/2021 ∙ by Ali Hasan, et al. ∙ 14 ∙ share

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On Statistical Efficiency in Learning

A central issue of many statistical learning problems is to select an ap...
12/24/2020 ∙ by Jie Ding, et al. ∙ 0 ∙ share

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Task-Aware Neural Architecture Search

The design of handcrafted neural networks requires a lot of time and res...
10/27/2020 ∙ by Cat P. Le, et al. ∙ 0 ∙ share

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HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

Federated Learning (FL) is a method of training machine learning models ...
10/03/2020 ∙ by Enmao Diao, et al. ∙ 0 ∙ share

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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...
07/13/2020 ∙ by Robert J. Ravier, et al. ∙ 0 ∙ share

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Deep Cross-Subject Mapping of Neural Activity

In this paper, we demonstrate that a neural decoder trained on neural ac...
07/13/2020 ∙ by Marko Angjelichinoski, et al. ∙ 0 ∙ share

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Projected Latent Markov Chain Monte Carlo: Conditional Inference with Normalizing Flows

We introduce Projected Latent Markov Chain Monte Carlo (PL-MCMC), a tech...
07/13/2020 ∙ by Chris Cannella, et al. ∙ 0 ∙ share

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Fisher Auto-Encoders

It has been conjectured that the Fisher divergence is more robust to mod...
07/12/2020 ∙ by Khalil Elkhalil, et al. ∙ 43 ∙ share

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Learning latent stochastic differential equations with variational auto-encoders

We present a method for learning latent stochastic differential equation...
07/12/2020 ∙ by Ali Hasan, et al. ∙ 0 ∙ share

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Model Linkage Selection for Cooperative Learning

Rapid developments in data collecting devices and computation platforms ...
05/15/2020 ∙ by Jiaying Zhou, et al. ∙ 0 ∙ share

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Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization

Various types of parameter restart schemes have been proposed for accele...
02/26/2020 ∙ by Yi Zhou, et al. ∙ 0 ∙ share

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Multimodal Controller for Generative Models

Class-conditional generative models are crucial tools for data generatio...
02/07/2020 ∙ by Enmao Diao, et al. ∙ 0 ∙ share

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Robust Marine Buoy Placement for Ship Detection Using Dropout K-Means

Marine buoys aid in the battle against Illegal, Unreported and Unregulat...
01/02/2020 ∙ by Yuting Ng, et al. ∙ 0 ∙ share

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A Distributed Online Convex Optimization Algorithm with Improved Dynamic Regret

In this paper, we consider the problem of distributed online convex opti...
11/12/2019 ∙ by Yan Zhang, et al. ∙ 0 ∙ share

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Cross-subject Decoding of Eye Movement Goals from Local Field Potentials

Objective. We consider the cross-subject decoding problem from local fie...
11/08/2019 ∙ by Marko Angjelichinoski, et al. ∙ 15 ∙ share

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Deep Clustering of Compressed Variational Embeddings

Motivated by the ever-increasing demands for limited communication bandw...
10/23/2019 ∙ by Suya Wu, et al. ∙ 0 ∙ share

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Learning Partial Differential Equations from Data Using Neural Networks

We develop a framework for estimating unknown partial differential equat...
10/22/2019 ∙ by Ali Hasan, et al. ∙ 0 ∙ share

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Perception-Distortion Trade-off with Restricted Boltzmann Machines

In this work, we introduce a new procedure for applying Restricted Boltz...
10/21/2019 ∙ by Chris Cannella, et al. ∙ 0 ∙ share

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Speech Emotion Recognition with Dual-Sequence LSTM Architecture

Speech Emotion Recognition (SER) has emerged as a critical component of ...
10/20/2019 ∙ by Jianyou Wang, et al. ∙ 0 ∙ share

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Restricted Recurrent Neural Networks

Recurrent Neural Network (RNN) and its variations such as Long Short-Ter...
08/21/2019 ∙ by Enmao Diao, et al. ∙ 0 ∙ share

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Distributed Lossy Image Compression with Recurrent Networks

We propose a new architecture for distributed image compression from a g...
03/23/2019 ∙ by Enmao Diao, et al. ∙ 0 ∙ share

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Convergence Rate of Empirical Spectral Distribution of Random Matrices from Linear Codes

It is known that the empirical spectral distribution of random matrices ...
02/22/2019 ∙ by Chin Hei Chan, et al. ∙ 0 ∙ share

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Momentum Schemes with Stochastic Variance Reduction for Nonconvex Composite Optimization

Two new stochastic variance-reduced algorithms named SARAH and SPIDER ha...
02/07/2019 ∙ by Yi Zhou, et al. ∙ 0 ∙ share

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Minimax-optimal decoding of movement goals from local field potentials using complex spectral features

We consider the problem of predicting eye movement goals from local fiel...
01/29/2019 ∙ by Marko Angjelichinoski, et al. ∙ 0 ∙ share

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SGD Converges to Global Minimum in Deep Learning via Star-convex Path

Stochastic gradient descent (SGD) has been found to be surprisingly effe...
01/02/2019 ∙ by Yi Zhou, et al. ∙ 18 ∙ share

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SpiderBoost: A Class of Faster Variance-reduced Algorithms for Nonconvex Optimization

There has been extensive research on developing stochastic variance redu...
10/25/2018 ∙ by Zhe Wang, et al. ∙ 9 ∙ share

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Model Selection Techniques -- An Overview

In the era of big data, analysts usually explore various statistical mod...
10/22/2018 ∙ by Jie Ding, et al. ∙ 0 ∙ share

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Learning Bounds for Greedy Approximation with Explicit Feature Maps from Multiple Kernels

Nonlinear kernels can be approximated using finite-dimensional feature m...
10/09/2018 ∙ by Shahin Shahrampour, et al. ∙ 0 ∙ share

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Sequential Detection of Regime Changes in Neural Data

The problem of detecting changes in firing patterns in neural data is st...
09/02/2018 ∙ by Taposh Banerjee, et al. ∙ 0 ∙ share

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Cyclostationary Statistical Models and Algorithms for Anomaly Detection Using Multi-Modal Data

A framework is proposed to detect anomalies in multi-modal data. A deep ...
07/02/2018 ∙ by Taposh Banerjee, et al. ∙ 0 ∙ share

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Stationary Geometric Graphical Model Selection

We consider the problem of model selection in Gaussian Markov fields in ...
06/10/2018 ∙ by Ilya Soloveychik, et al. ∙ 0 ∙ share

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Sequential Event Detection Using Multimodal Data in Nonstationary Environments

The problem of sequential detection of anomalies in multimodal data is c...
03/23/2018 ∙ by Taposh Banerjee, et al. ∙ 0 ∙ share

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Evolutionary Spectra Based on the Multitaper Method with Application to Stationarity Test

In this work, we propose a new inference procedure for understanding non...
02/25/2018 ∙ by Yu Xiang, et al. ∙ 0 ∙ share

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Region Detection in Markov Random Fields: Gaussian Case

In this work we consider the problem of model selection in Gaussian Mark...
02/12/2018 ∙ by Ilya Soloveychik, et al. ∙ 0 ∙ share

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On Data-Dependent Random Features for Improved Generalization in Supervised Learning

The randomized-feature approach has been successfully employed in large-...
12/19/2017 ∙ by Shahin Shahrampour, et al. ∙ 0 ∙ share

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On Optimal Generalizability in Parametric Learning

We consider the parametric learning problem, where the objective of the ...
11/14/2017 ∙ by Ahmad Beirami, et al. ∙ 0 ∙ share

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Wavelet Shrinkage and Thresholding based Robust Classification for Brain Computer Interface

A macaque monkey is trained to perform two different kinds of tasks, mem...
10/27/2017 ∙ by Taposh Banerjee, et al. ∙ 0 ∙ share

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Dictionary Learning and Sparse Coding-based Denoising for High-Resolution Task Functional Connectivity MRI Analysis

We propose a novel denoising framework for task functional Magnetic Reso...
07/21/2017 ∙ by Seongah Jeong, et al. ∙ 0 ∙ share

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Nonlinear Sequential Accepts and Rejects for Identification of Top Arms in Stochastic Bandits

We address the M-best-arm identification problem in multi-armed bandits....
07/09/2017 ∙ by Shahin Shahrampour, et al. ∙ 0 ∙ share

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On Sequential Elimination Algorithms for Best-Arm Identification in Multi-Armed Bandits

We consider the best-arm identification problem in multi-armed bandits, ...
09/08/2016 ∙ by Shahin Shahrampour, et al. ∙ 0 ∙ share

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Learning the Number of Autoregressive Mixtures in Time Series Using the Gap Statistics

Using a proper model to characterize a time series is crucial in making ...
09/11/2015 ∙ by Jie Ding, et al. ∙ 0 ∙ share

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Bridging AIC and BIC: a new criterion for autoregression

We introduce a new criterion to determine the order of an autoregressive...
08/11/2015 ∙ by Jie Ding, et al. ∙ 0 ∙ share

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Vahid Tarokh

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