California Institute of Technology

∙ Pasadena , United States ∙ 0 followers

The California Institute of Technology is a private doctorate-granting research university located in Pasadena, California, United States.

Implicit competitive regularization in GANs

Generative adversarial networks (GANs) are capable of producing high qua...
10/13/2019 ∙ by Florian Schäfer, et al. ∙ 49 ∙ share

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Out-of-Distribution Detection Using Neural Rendering Generative Models

Out-of-distribution (OoD) detection is a natural downstream task for dee...
07/10/2019 ∙ by Yujia Huang, et al. ∙ 35 ∙ share

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FERAtt: Facial Expression Recognition with Attention Net

We present a new end-to-end network architecture for facial expression r...
02/08/2019 ∙ by Pedro D. Marrero Fernandez, et al. ∙ 28 ∙ share

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Learning Calibratable Policies using Programmatic Style-Consistency

We study the important and challenging problem of controllable generatio...
10/02/2019 ∙ by Eric Zhan, et al. ∙ 21 ∙ share

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Physicist's Journeys Through the AI World - A Topical Review. There is no royal road to unsupervised learning

Artificial Intelligence (AI), defined in its most simple form, is a tech...
05/02/2019 ∙ by Imad Alhousseini, et al. ∙ 18 ∙ share

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SLM Lab: A Comprehensive Benchmark and Modular Software Framework for Reproducible Deep Reinforcement Learning

We introduce SLM Lab, a software framework for reproducible reinforcemen...
12/28/2019 ∙ by Keng Wah Loon, et al. ∙ 16 ∙ share

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Plug and Play Language Models: a Simple Approach to Controlled Text Generation

Large transformer-based language models (LMs) trained on huge text corpo...
12/04/2019 ∙ by Sumanth Dathathri, et al. ∙ 13 ∙ share

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A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes

How can we efficiently gather information to optimize an unknown functio...
11/02/2018 ∙ by Jialin Song, et al. ∙ 12 ∙ share

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A General Method for Amortizing Variational Filtering

We introduce the variational filtering EM algorithm, a simple, general-p...
11/13/2018 ∙ by Joseph Marino, et al. ∙ 12 ∙ share

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Deep Metric Structured Learning For Facial Expression Recognition

We propose a deep metric learning model to create embedded sub-spaces wi...
01/18/2020 ∙ by Pedro D. Marrero Fernandez, et al. ∙ 12 ∙ share

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Risk-Averse Planning Under Uncertainty

We consider the problem of designing policies for partially observable M...
09/27/2019 ∙ by Mohamadreza Ahmadi, et al. ∙ 11 ∙ share

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HMM-guided frame querying for bandwidth-constrained video search

We design an agent to search for frames of interest in video stored on a...
12/31/2019 ∙ by Bhairav Chidambaram, et al. ∙ 11 ∙ share

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Using Data Imputation for Signal Separation in High Contrast Imaging

To characterize circumstellar systems in high contrast imaging, the fund...
01/02/2020 ∙ by Bin Ren, et al. ∙ 10 ∙ share

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Consistent Robust Adversarial Prediction for General Multiclass Classification

We propose a robust adversarial prediction framework for general multicl...
12/18/2018 ∙ by Rizal Fathony, et al. ∙ 8 ∙ share

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A Stochastic Interpretation of Stochastic Mirror Descent: Risk-Sensitive Optimality

Stochastic mirror descent (SMD) is a fairly new family of algorithms tha...
04/03/2019 ∙ by Navid Azizan, et al. ∙ 6 ∙ share

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Recognition in Terra Incognita

It is desirable for detection and classification algorithms to generaliz...
07/13/2018 ∙ by Sara Beery, et al. ∙ 4 ∙ share

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Analysis Of Momentum Methods

Gradient decent-based optimization methods underpin the parameter traini...
06/10/2019 ∙ by Nikola B. Kovachki, et al. ∙ 4 ∙ share

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Approximate Causal Abstraction

Scientific models describe natural phenomena at different levels of abst...
06/27/2019 ∙ by Sander Beckers, et al. ∙ 4 ∙ share

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Rules of the Road: Predicting Driving Behavior with a Convolutional Model of Semantic Interactions

We focus on the problem of predicting future states of entities in compl...
06/21/2019 ∙ by Joey Hong, et al. ∙ 3 ∙ share

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Kernel Mode Decomposition and programmable/interpretable regression networks

Mode decomposition is a prototypical pattern recognition problem that ca...
07/19/2019 ∙ by Houman Owhadi, et al. ∙ 3 ∙ share

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Open Vocabulary Learning on Source Code with a Graph-Structured Cache

Machine learning models that take computer program source code as input ...
10/18/2018 ∙ by Milan Cvitkovic, et al. ∙ 2 ∙ share

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ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions

In recent years the possibility of relaxing the so-called Faithfulness a...
06/06/2019 ∙ by Zhalama, et al. ∙ 2 ∙ share

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Robust Regression for Safe Exploration in Control

We study the problem of safe learning and exploration in sequential cont...
06/13/2019 ∙ by Anqi Liu, et al. ∙ 1 ∙ share

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Improving the Robustness of Deep Neural Networks via Stability Training

In this paper we address the issue of output instability of deep neural ...
04/15/2016 ∙ by Stephan Zheng, et al. ∙ 0 ∙ share

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Quantifying Performance of Bipedal Standing with Multi-channel EMG

Spinal cord stimulation has enabled humans with motor complete spinal co...
11/21/2017 ∙ by Yanan Sui, et al. ∙ 0 ∙ share

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A Parallelizable Acceleration Framework for Packing Linear Programs

This paper presents an acceleration framework for packing linear program...
11/17/2017 ∙ by Palma London, et al. ∙ 0 ∙ share

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Meta Inverse Reinforcement Learning via Maximum Reward Sharing for Human Motion Analysis

This work handles the inverse reinforcement learning (IRL) problem where...
10/07/2017 ∙ by Kun Li, et al. ∙ 0 ∙ share

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Bayesian Optimization for Parameter Tuning of the XOR Neural Network

When applying Machine Learning techniques to problems, one must select m...
09/22/2017 ∙ by Lawrence Stewart, et al. ∙ 0 ∙ share

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SEGMENT3D: A Web-based Application for Collaborative Segmentation of 3D images used in the Shoot Apical Meristem

The quantitative analysis of 3D confocal microscopy images of the shoot ...
10/26/2017 ∙ by Thiago V. Spina, et al. ∙ 0 ∙ share

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Effective Image Differencing with ConvNets for Real-time Transient Hunting

Large sky surveys are increasingly relying on image subtraction pipeline...
10/04/2017 ∙ by Nima Sedaghat, et al. ∙ 0 ∙ share

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Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations

Climate projections continue to be marred by large uncertainties, which ...
08/31/2017 ∙ by Tapio Schneider, et al. ∙ 0 ∙ share

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Deep-Learnt Classification of Light Curves

Astronomy light curves are sparse, gappy, and heteroscedastic. As a resu...
09/19/2017 ∙ by Ashish Mahabal, et al. ∙ 0 ∙ share

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On the enumeration of sentences by compactness

Presented is a Julia meta-program that discovers compact theories from d...
06/15/2017 ∙ by Mark A. Stalzer, et al. ∙ 0 ∙ share

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Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting

Spatiotemporal forecasting has various applications in neuroscience, cli...
07/06/2017 ∙ by Yaguang Li, et al. ∙ 0 ∙ share

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Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data

Several important applications, such as streaming PCA and semidefinite p...
06/18/2017 ∙ by Joel A. Tropp, et al. ∙ 0 ∙ share

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What your Facebook Profile Picture Reveals about your Personality

People spend considerable effort managing the impressions they give othe...
08/03/2017 ∙ by Cristina Segalin, et al. ∙ 0 ∙ share

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Genetic optimization of the Hyperloop route through the Grapevine

We demonstrate a genetic algorithm that employs a versatile fitness func...
03/05/2015 ∙ by Casey J. Handmer, et al. ∙ 0 ∙ share

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Clinical Patient Tracking in the Presence of Transient and Permanent Occlusions via Geodesic Feature

This paper develops a method to use RGB-D cameras to track the motions o...
07/22/2017 ∙ by Kun Li, et al. ∙ 0 ∙ share

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Benchmarking and Error Diagnosis in Multi-Instance Pose Estimation

We propose a new method to analyze the impact of errors in algorithms fo...
07/17/2017 ∙ by Matteo Ruggero Ronchi, et al. ∙ 0 ∙ share

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Reinforcement Learning in Rich-Observation MDPs using Spectral Methods

Designing effective exploration-exploitation algorithms in Markov decisi...
11/11/2016 ∙ by Kamyar Azizzadenesheli, et al. ∙ 0 ∙ share

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Uncertainty Quantification in the Classification of High Dimensional Data

Classification of high dimensional data finds wide-ranging applications....
03/26/2017 ∙ by Andrea L. Bertozzi, et al. ∙ 0 ∙ share

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Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery

High-Throughput materials discovery involves the rapid synthesis, measur...
10/03/2016 ∙ by Yexiang Xue, et al. ∙ 0 ∙ share

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Synthesis of Stochastic Flow Networks

A stochastic flow network is a directed graph with incoming edges (input...
09/04/2012 ∙ by Hongchao Zhou, et al. ∙ 0 ∙ share

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Parameter Selection Algorithm For Continuous Variables

In this article, we propose a new algorithm for supervised learning meth...
01/19/2017 ∙ by Peyman Tavallali, et al. ∙ 0 ∙ share

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A Matrix Factorization Approach for Learning Semidefinite-Representable Regularizers

Regularization techniques are widely employed in optimization-based appr...
01/05/2017 ∙ by Yong Sheng Soh, et al. ∙ 0 ∙ share

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Causal Discovery from Subsampled Time Series Data by Constraint Optimization

This paper focuses on causal structure estimation from time series data ...
02/25/2016 ∙ by Antti Hyttinen, et al. ∙ 0 ∙ share

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The Possibilities and Limitations of Private Prediction Markets

We consider the design of private prediction markets, financial markets ...
02/24/2016 ∙ by Rachel Cummings, et al. ∙ 0 ∙ share

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Adaptive evolution on neutral networks

We study the evolution of large but finite asexual populations evolving ...
01/03/2001 ∙ by Claus O. Wilke, et al. ∙ 0 ∙ share

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Randomized single-view algorithms for low-rank matrix approximation

This paper develops a suite of algorithms for constructing low-rank appr...
08/31/2016 ∙ by Joel A. Tropp, et al. ∙ 0 ∙ share

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Gamblets for opening the complexity-bottleneck of implicit schemes for hyperbolic and parabolic ODEs/PDEs with rough coefficients

Implicit schemes are popular methods for the integration of time depende...
06/24/2016 ∙ by Houman Owhadi, et al. ∙ 0 ∙ share

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