University of Colorado Boulder

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The University of Colorado Boulder is a public research university located in Boulder, Colorado, United States.

Tensor Embedding: A Supervised Framework for Human Behavioral Data Mining and Prediction

Today's densely instrumented world offers tremendous opportunities for c...
08/31/2018 ∙ by Homa Hosseinmardi, et al. ∙ 16 ∙ share

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Virtual-to-Real-World Transfer Learning for Robots on Wilderness Trails

Robots hold promise in many scenarios involving outdoor use, such as sea...
01/17/2019 ∙ by Michael L. Iuzzolino, et al. ∙ 14 ∙ share

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Stochastic Substitute Training: A Gray-box Approach to Craft Adversarial Examples Against Gradient Obfuscation Defenses

It has been shown that adversaries can craft example inputs to neural ne...
10/23/2018 ∙ by Mohammad Hashemi, et al. ∙ 12 ∙ share

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"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans

To support human decision making with machine learning models, we often ...
01/14/2020 ∙ by Vivian Lai, et al. ∙ 8 ∙ share

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On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection

Humans are the final decision makers in critical tasks that involve ethi...
11/19/2018 ∙ by Vivian Lai, et al. ∙ 6 ∙ share

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Interactive Learning for Identifying Relevant Tweets to Support Real-time Situational Awareness

Various domain users are increasingly leveraging real-time social media ...
08/01/2019 ∙ by Luke S. Snyder, et al. ∙ 5 ∙ share

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Equal Opportunity in Online Classification with Partial Feedback

We study an online classification problem with partial feedback in which...
02/06/2019 ∙ by Yahav Bechavod, et al. ∙ 4 ∙ share

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Decentralized & Collaborative AI on Blockchain

Machine learning has recently enabled large advances in artificial intel...
07/16/2019 ∙ by Justin D. Harris, et al. ∙ 3 ∙ share

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A tunable multiresolution smoother for scattered data with application to particle filtering

A smoothing algorithm is presented that can reduce the small-scale conte...
06/16/2019 ∙ by Gregor A. Robinson, et al. ∙ 1 ∙ share

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Online Red Packets: A Large-scale Empirical Study of Gift Giving on WeChat

Gift giving is a ubiquitous social phenomenon, and red packets have been...
12/08/2017 ∙ by Yuan Yuan, et al. ∙ 0 ∙ share

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Discrete Event, Continuous Time RNNs

We investigate recurrent neural network architectures for event-sequence...
10/11/2017 ∙ by Michael C. Mozer, et al. ∙ 0 ∙ share

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"Dave...I can assure you...that it's going to be all right..." -- A definition, case for, and survey of algorithmic assurances in human-autonomy trust relationships

As technology becomes more advanced, those who design, use and are other...
11/08/2017 ∙ by Brett W Israelsen, et al. ∙ 0 ∙ share

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Characterizing the structural diversity of complex networks across domains

The structure of complex networks has been of interest in many scientifi...
10/31/2017 ∙ by Kansuke Ikehara, et al. ∙ 0 ∙ share

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Improving Human-Machine Cooperative Visual Search With Soft Highlighting

Advances in machine learning have produced systems that attain human-lev...
12/24/2016 ∙ by Ronald T. Kneusel, et al. ∙ 0 ∙ share

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"I can assure you [...] that it's going to be all right" -- A definition, case for, and survey of algorithmic assurances in human-autonomy trust relationships

As technology become more advanced, those who design, use and are otherw...
08/01/2017 ∙ by Brett W Israelsen, et al. ∙ 0 ∙ share

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Preconditioned Spectral Clustering for Stochastic Block Partition Streaming Graph Challenge

Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) is demo...
08/21/2017 ∙ by David Zhuzhunashvili, et al. ∙ 0 ∙ share

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Improved Fixed-Rank Nyström Approximation via QR Decomposition: Practical and Theoretical Aspects

The Nyström method is a popular technique for computing fixed-rank appro...
08/08/2017 ∙ by Farhad Pourkamali-Anaraki, et al. ∙ 0 ∙ share

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How deep is knowledge tracing?

In theoretical cognitive science, there is a tension between highly stru...
03/14/2016 ∙ by Mohammad Khajah, et al. ∙ 0 ∙ share

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A Neural Framework for Generalized Topic Models

Topic models for text corpora comprise a popular family of methods that ...
05/25/2017 ∙ by Dallas Card, et al. ∙ 0 ∙ share

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Classifying Graphs as Images with Convolutional Neural Networks

The task of graph classification is currently dominated by graph kernels...
07/29/2017 ∙ by Antoine Jean-Pierre Tixier, et al. ∙ 0 ∙ share

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Hybrid Repeat/Multi-point Sampling for Highly Volatile Objective Functions

A key drawback of the current generation of artificial decision-makers i...
12/13/2016 ∙ by Brett Israelsen, et al. ∙ 0 ∙ share

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Randomized Clustered Nystrom for Large-Scale Kernel Machines

The Nystrom method has been popular for generating the low-rank approxim...
12/20/2016 ∙ by Farhad Pourkamali-Anaraki, et al. ∙ 0 ∙ share

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A Signaling Game Approach to Databases Querying and Interaction

As most database users cannot precisely express their information needs,...
03/13/2016 ∙ by Ben McCamish, et al. ∙ 0 ∙ share

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The ground truth about metadata and community detection in networks

Across many scientific domains, there is a common need to automatically ...
08/20/2016 ∙ by Leto Peel, et al. ∙ 0 ∙ share

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Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game

Interpersonal relations are fickle, with close friendships often dissolv...
06/15/2015 ∙ by Vlad Niculae, et al. ∙ 0 ∙ share

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Dual Smoothing and Level Set Techniques for Variational Matrix Decomposition

We focus on the robust principal component analysis (RPCA) problem, and ...
03/01/2016 ∙ by Aleksandr Y. Aravkin, et al. ∙ 0 ∙ share

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Estimation of the sample covariance matrix from compressive measurements

This paper focuses on the estimation of the sample covariance matrix fro...
12/30/2015 ∙ by Farhad Pourkamali-Anaraki, et al. ∙ 0 ∙ share

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Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means

We analyze a compression scheme for large data sets that randomly keeps ...
10/31/2015 ∙ by Farhad Pourkamali-Anaraki, et al. ∙ 0 ∙ share

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Detectability thresholds and optimal algorithms for community structure in dynamic networks

We study the fundamental limits on learning latent community structure i...
06/19/2015 ∙ by Amir Ghasemian, et al. ∙ 0 ∙ share

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Efficient Dictionary Learning via Very Sparse Random Projections

Performing signal processing tasks on compressive measurements of data h...
04/05/2015 ∙ by Farhad Pourkamali-Anaraki, et al. ∙ 0 ∙ share

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A unified view of generative models for networks: models, methods, opportunities, and challenges

Research on probabilistic models of networks now spans a wide variety of...
11/14/2014 ∙ by Abigail Z. Jacobs, et al. ∙ 0 ∙ share

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An Efficient Search Strategy for Aggregation and Discretization of Attributes of Bayesian Networks Using Minimum Description Length

Bayesian networks are convenient graphical expressions for high dimensio...
04/03/2014 ∙ by Jem Corcoran, et al. ∙ 0 ∙ share

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Learning Latent Block Structure in Weighted Networks

Community detection is an important task in network analysis, in which w...
04/02/2014 ∙ by Christopher Aicher, et al. ∙ 0 ∙ share

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Detecting change points in the large-scale structure of evolving networks

Interactions among people or objects are often dynamic in nature and can...
03/05/2014 ∙ by Leto Peel, et al. ∙ 0 ∙ share

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Loosely Coupled Formulations for Automated Planning: An Integer Programming Perspective

We represent planning as a set of loosely coupled network flow problems,...
10/31/2011 ∙ by Menkes Hector Louis van den Briel, et al. ∙ 0 ∙ share

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Active Discovery of Network Roles for Predicting the Classes of Network Nodes

Nodes in real world networks often have class labels, or underlying attr...
12/27/2013 ∙ by Leto Peel, et al. ∙ 0 ∙ share

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Adapting the Stochastic Block Model to Edge-Weighted Networks

We generalize the stochastic block model to the important case in which ...
05/24/2013 ∙ by Christopher Aicher, et al. ∙ 0 ∙ share

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Inverting Nonlinear Dimensionality Reduction with Scale-Free Radial Basis Function Interpolation

Nonlinear dimensionality reduction embeddings computed from datasets do ...
05/01/2013 ∙ by Nathan D. Monnig, et al. ∙ 0 ∙ share

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Keeping greed good: sparse regression under design uncertainty with application to biomass characterization

In this paper, we consider the classic measurement error regression scen...
07/08/2012 ∙ by David J. Biagioni, et al. ∙ 0 ∙ share

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Online SLAM with Any-time Self-calibration and Automatic Change Detection

A framework for online simultaneous localization, mapping and self-calib...
11/05/2014 ∙ by Nima Keivan, et al. ∙ 0 ∙ share

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Simultaneous Localization, Mapping, and Manipulation for Unsupervised Object Discovery

We present an unsupervised framework for simultaneous appearance-based o...
11/04/2014 ∙ by Lu Ma, et al. ∙ 0 ∙ share

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Non-Asymptotic Analysis of Tangent Space Perturbation

Constructing an efficient parameterization of a large, noisy data set of...
11/20/2011 ∙ by Daniel N. Kaslovsky, et al. ∙ 0 ∙ share

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A random walk on image patches

In this paper we address the problem of understanding the success of alg...
07/02/2011 ∙ by Kye M. Taylor, et al. ∙ 0 ∙ share

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Adapting to Non-stationarity with Growing Expert Ensembles

When dealing with time series with complex non-stationarities, low retro...
03/04/2011 ∙ by Cosma Rohilla Shalizi, et al. ∙ 0 ∙ share

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Coherence, Belief Expansion and Bayesian Networks

We construct a probabilistic coherence measure for information sets whic...
03/08/2000 ∙ by Luc Bovens, et al. ∙ 0 ∙ share

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Locality and low-dimensions in the prediction of natural experience from fMRI

Functional Magnetic Resonance Imaging (fMRI) provides dynamical access i...
12/07/2007 ∙ by Francois G. Meyer, et al. ∙ 0 ∙ share

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Low Dimensional Embedding of fMRI datasets

We propose a novel method to embed a functional magnetic resonance imagi...
09/19/2007 ∙ by Xilin Shen, et al. ∙ 0 ∙ share

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Autocomplete Textures for 3D Printing

Texture is an essential property of physical objects that affects aesthe...
03/16/2017 ∙ by Ryo Suzuki, et al. ∙ 0 ∙ share

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Coping with Construals in Broad-Coverage Semantic Annotation of Adpositions

We consider the semantics of prepositions, revisiting a broad-coverage a...
03/10/2017 ∙ by Jena D. Hwang, et al. ∙ 0 ∙ share

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A corpus of preposition supersenses in English web reviews

We present the first corpus annotated with preposition supersenses, unle...
05/08/2016 ∙ by Nathan Schneider, et al. ∙ 0 ∙ share

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