
Machine: The New Art Connoisseur
The process of identifying and understanding art styles to discover arti...
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Leveraging SemiSupervised Learning for Fairness using Neural Networks
There has been a growing concern about the fairness of decisionmaking s...
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Combined convolutional and recurrent neural networks for hierarchical classification of images
Deep learning models based on CNNs are predominantly used in image class...
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Smoothed Analysis in Unsupervised Learning via Decoupling
Smoothed analysis is a powerful paradigm in overcoming worstcase intrac...
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Transfer Learning Using Ensemble Neural Nets for Organic Solar Cell Screening
Organic Solar Cells are a promising technology for solving the clean ene...
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Deep Learning: a new definition of artificial neuron with double weight
Deep learning is a subset of a broader family of machine learning method...
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Eavesdrop the Composition Proportion of Training Labels in Federated Learning
Federated learning (FL) has recently emerged as a new form of collaborat...
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A realtime iterative machine learning approach for temperature profile prediction in additive manufacturing processes
Additive Manufacturing (AM) is a manufacturing paradigm that builds thre...
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Unified recurrent neural network for many feature types
There are time series that are amenable to recurrent neural network (RNN...
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Fully Implicit Online Learning
Regularized online learning is widely used in machine learning. In this ...
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Keywordbased Topic Modeling and Keyword Selection
Certain type of documents such as tweets are collected by specifying a s...
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High Fidelity Vector Space Models of Structured Data
Machine learning systems regularly deal with structured data in realwor...
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Listwise Learning to Rank by Exploring Unique Ratings
In this paper, we propose new listwise learningtorank models that miti...
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Forecasting Crime with Deep Learning
The objective of this work is to take advantage of deep neural networks ...
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IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery
Materials discovery is crucial for making scientific advances in many do...
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Uncalibrated Deflectometry with a Mobile Device on Extended Specular Surfaces
We introduce a system and methods for the threedimensional measurement ...
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Eventdriven Video Frame Synthesis
Video frame synthesis is an active computer vision problem which has app...
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Instance Enhancement Batch Normalization: an Adaptive Regulator of Batch Noise
Batch Normalization (BN) (Ioffe and Szegedy 2015) normalizes the feature...
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DeepBinaryMask: Learning a Binary Mask for Video Compressive Sensing
In this paper, we propose a novel encoderdecoder neural network model r...
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Deep FullyConnected Networks for Video Compressive Sensing
In this work we present a deep learning framework for video compressive ...
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Photometric Stereo by UVInduced Fluorescence to Detect Protrusions on Georgia O'Keeffe's Paintings
A significant number of oil paintings produced by Georgia O'Keeffe (1887...
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Computational multifocal microscopy
Despite recent advances, high performance singleshot 3D microscopy rema...
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Mixturebased Multiple Imputation Models for Clinical Data with a Temporal Dimension
The problem of missing values in multivariable time series is a key chal...
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AI Safety and Reproducibility: Establishing Robust Foundations for the Neuroscience of Human Values
We propose the creation of a systematic effort to identify and replicate...
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L1norm Kernel PCA
We present the first model and algorithm for L1norm kernel PCA. While L...
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Property Testing in High Dimensional Ising models
This paper explores the informationtheoretic limitations of graph prope...
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A Robust MultiBatch LBFGS Method for Machine Learning
This paper describes an implementation of the LBFGS method designed to ...
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SEVEN: Deep Semisupervised Verification Networks
Verification determines whether two samples belong to the same class or ...
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Improving the Expected Improvement Algorithm
The expected improvement (EI) algorithm is a popular strategy for inform...
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An Investigation of NewtonSketch and Subsampled Newton Methods
The concepts of sketching and subsampling have recently received much at...
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Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision
Harnessing the statistical power of neural networks to perform language ...
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Subset Selection for Multiple Linear Regression via Optimization
Subset selection in multiple linear regression is to choose a subset of ...
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Patchwork Kriging for Largescale Gaussian Process Regression
This paper presents a new approach for Gaussian process (GP) regression ...
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Bayesian Network Learning via Topological Order
We propose a mixed integer programming (MIP) model and iterative algorit...
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Detach and Adapt: Learning CrossDomain Disentangled Deep Representation
While representation learning aims to derive interpretable features for ...
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Creativity: Generating Diverse Questions using Variational Autoencoders
Generating diverse questions for given images is an important task for c...
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Optimization for LargeScale Machine Learning with Distributed Features and Observations
As the size of modern data sets exceeds the disk and memory capacities o...
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A Primer on Coordinate Descent Algorithms
This monograph presents a class of algorithms called coordinate descent ...
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GeometryBased Region Proposals for RealTime Robot Detection of Tabletop Objects
We present a novel object detection pipeline for localization and recogn...
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Comment on "Why does deep and cheap learning work so well?" [arXiv:1608.08225]
In a recent paper, "Why does deep and cheap learning work so well?", Lin...
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Iteratively Reweighted Least Squares Algorithms for L1Norm Principal Component Analysis
Principal component analysis (PCA) is often used to reduce the dimension...
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Qualitative Decision Methods for MultiAttribute Decision Making
The fundamental problem underlying all multicriteria decision analysis ...
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Combining Random Walks and Nonparametric Bayesian Topic Model for Community Detection
Community detection has been an active research area for decades. Among ...
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Algorithms for Generalized Clusterwise Linear Regression
Clusterwise linear regression (CLR), a clustering problem intertwined w...
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An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning
We propose a clusteringbased iterative algorithm to solve certain optim...
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A MultiBatch LBFGS Method for Machine Learning
The question of how to parallelize the stochastic gradient descent (SGD)...
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A logic for reasoning about ambiguity
Standard models of multiagent modal logic do not capture the fact that ...
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Mining Brain Networks using Multiple Side Views for Neurological Disorder Identification
Mining discriminative subgraph patterns from graph data has attracted gr...
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Walk and Learn: Facial Attribute Representation Learning from Egocentric Video and Contextual Data
The way people look in terms of facial attributes (ethnicity, hair color...
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Quantifying mesoscale neuroanatomy using Xray microtomography
Methods for resolving the 3D microstructure of the brain typically start...
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Northwestern University
Northwestern University is a private research university based in Evanston, Illinois, United States, with other campuses located in Chicago and Doha, Qatar, and academic programs and facilities in Miami, Florida; Washington, DC; and San Francisco, Cali...