University of California Santa Cruz

∙ Santa Cruz , United States ∙ 0 followers

A world-class public research institution comprised of ten residential college communities nestled in the redwood forests and meadows overlooking central California's Monterey Bay.

Using Image Priors to Improve Scene Understanding

Semantic segmentation algorithms that can robustly segment objects acros...
10/02/2019 ∙ by Brigit Schroeder, et al. ∙ 46 ∙ share

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Correcting the bias in least squares regression with volume-rescaled sampling

Consider linear regression where the examples are generated by an unknow...
10/04/2018 ∙ by Michal Derezinski, et al. ∙ 38 ∙ share

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Estimating Aggregate Properties In Relational Networks With Unobserved Data

Aggregate network properties such as cluster cohesion and the number of ...
01/16/2020 ∙ by Varun Embar, et al. ∙ 24 ∙ share

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Replication Markets: Results, Lessons, Challenges and Opportunities in AI Replication

The last decade saw the emergence of systematic large-scale replication ...
05/10/2020 ∙ by Yang Liu, et al. ∙ 12 ∙ share

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Incentives for Federated Learning: a Hypothesis Elicitation Approach

Federated learning provides a promising paradigm for collecting machine ...
07/21/2020 ∙ by Yang Liu, et al. ∙ 10 ∙ share

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Hopfield Neural Network Flow: A Geometric Viewpoint

We provide gradient flow interpretations for the continuous-time continu...
08/04/2019 ∙ by Abhishek Halder, et al. ∙ 9 ∙ share

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Private Stochastic Convex Optimization with Optimal Rates

We study differentially private (DP) algorithms for stochastic convex op...
08/27/2019 ∙ by Raef Bassily, et al. ∙ 9 ∙ share

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A Gaussian Process Upsampling Model for Improvements in Optical Character Recognition

Optical Character Recognition and extraction is a key tool in the automa...
05/07/2020 ∙ by Steven I Reeves, et al. ∙ 9 ∙ share

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Reinforcement Learning with Perturbed Rewards

Recent studies have shown the vulnerability of reinforcement learning (R...
10/02/2018 ∙ by Jingkang Wang, et al. ∙ 8 ∙ share

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User Profiling Using Hinge-loss Markov Random Fields

A variety of approaches have been proposed to automatically infer the pr...
01/05/2020 ∙ by Golnoosh Farnadi, et al. ∙ 6 ∙ share

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Structured Query-Based Image Retrieval Using Scene Graphs

A structured query can capture the complexity of object interactions (e....
05/13/2020 ∙ by Brigit Schroeder, et al. ∙ 6 ∙ share

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Obliviousness Makes Poisoning Adversaries Weaker

Poisoning attacks have emerged as a significant security threat to machi...
03/26/2020 ∙ by Sanjam Garg, et al. ∙ 5 ∙ share

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Scalable Structure Learning for Probabilistic Soft Logic

Statistical relational frameworks such as Markov logic networks and prob...
07/03/2018 ∙ by Varun Embar, et al. ∙ 4 ∙ share

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Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity

Sensitive statistics are often collected across sets of users, with repe...
11/29/2018 ∙ by Úlfar Erlingsson, et al. ∙ 4 ∙ share

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Unbiased estimators for random design regression

In linear regression we wish to estimate the optimum linear least square...
07/08/2019 ∙ by Michał Dereziński, et al. ∙ 4 ∙ share

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Time-Invariant LDPC Convolutional Codes

Spatially coupled codes have been shown to universally achieve the capac...
02/15/2017 ∙ by Dimitris Achlioptas, et al. ∙ 0 ∙ share

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Dynamic Influence Networks for Rule-based Models

We introduce the Dynamic Influence Network (DIN), a novel visual analyti...
11/02/2017 ∙ by Angus G. Forbes, et al. ∙ 0 ∙ share

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Learning User Intent from Action Sequences on Interactive Systems

Interactive systems have taken over the web and mobile space with increa...
12/04/2017 ∙ by Rakshit Agrawal, et al. ∙ 0 ∙ share

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Using Noisy Extractions to Discover Causal Knowledge

Knowledge bases (KB) constructed through information extraction from tex...
11/16/2017 ∙ by Dhanya Sridhar, et al. ∙ 0 ∙ share

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Modelling Protagonist Goals and Desires in First-Person Narrative

Many genres of natural language text are narratively structured, a testa...
08/29/2017 ∙ by Elahe Rahimtoroghi, et al. ∙ 0 ∙ share

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Inference of Fine-Grained Event Causality from Blogs and Films

Human understanding of narrative is mainly driven by reasoning about cau...
08/30/2017 ∙ by Zhichao Hu, et al. ∙ 0 ∙ share

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Learning Fine-Grained Knowledge about Contingent Relations between Everyday Events

Much of the user-generated content on social media is provided by ordina...
08/30/2017 ∙ by Elahe Rahimtoroghi, et al. ∙ 0 ∙ share

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Automatic Mapping of NES Games with Mappy

Game maps are useful for human players, general-game-playing agents, and...
07/12/2017 ∙ by Joseph C. Osborn, et al. ∙ 0 ∙ share

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Mechanics Automatically Recognized via Interactive Observation: Jumping

Jumping has been an important mechanic since its introduction in Donkey ...
07/12/2017 ∙ by Adam Summerville, et al. ∙ 0 ∙ share

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CHARDA: Causal Hybrid Automata Recovery via Dynamic Analysis

We propose and evaluate a new technique for learning hybrid automata aut...
07/11/2017 ∙ by Adam Summerville, et al. ∙ 0 ∙ share

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Automated Game Design Learning

While general game playing is an active field of research, the learning ...
07/11/2017 ∙ by Joseph C. Osborn, et al. ∙ 0 ∙ share

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Super Mario as a String: Platformer Level Generation Via LSTMs

The procedural generation of video game levels has existed for at least ...
03/02/2016 ∙ by Adam Summerville, et al. ∙ 0 ∙ share

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Surprising properties of dropout in deep networks

We analyze dropout in deep networks with rectified linear units and the ...
02/14/2016 ∙ by David P. Helmbold, et al. ∙ 0 ∙ share

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I Probe, Therefore I Am: Designing a Virtual Journalist with Human Emotions

By utilizing different communication channels, such as verbal language, ...
05/18/2017 ∙ by Kevin K. Bowden, et al. ∙ 0 ∙ share

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BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies

We propose BlackOut, an approximation algorithm to efficiently train mas...
11/21/2015 ∙ by Shihao Ji, et al. ∙ 0 ∙ share

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Procedural Content Generation via Machine Learning (PCGML)

This survey explores Procedural Content Generation via Machine Learning ...
02/02/2017 ∙ by Adam Summerville, et al. ∙ 0 ∙ share

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Two-temperature logistic regression based on the Tsallis divergence

We develop a variant of multiclass logistic regression that achieves thr...
05/19/2017 ∙ by Ehsan Amid, et al. ∙ 0 ∙ share

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On the Inductive Bias of Dropout

Dropout is a simple but effective technique for learning in neural netwo...
12/15/2014 ∙ by David P. Helmbold, et al. ∙ 0 ∙ share

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Low-dimensional Data Embedding via Robust Ranking

We describe a new method called t-ETE for finding a low-dimensional embe...
11/30/2016 ∙ by Ehsan Amid, et al. ∙ 0 ∙ share

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Learning From Graph Neighborhoods Using LSTMs

Many prediction problems can be phrased as inferences over local neighbo...
11/21/2016 ∙ by Rakshit Agrawal, et al. ∙ 0 ∙ share

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Bayesian Non-Homogeneous Markov Models via Polya-Gamma Data Augmentation with Applications to Rainfall Modeling

Discrete-time hidden Markov models are a broadly useful class of latent-...
01/11/2017 ∙ by Tracy Holsclaw, et al. ∙ 0 ∙ share

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Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

We introduce an algorithm for word-level text spotting that is able to a...
04/03/2017 ∙ by Siyang Qin, et al. ∙ 0 ∙ share

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Hinge-Loss Markov Random Fields and Probabilistic Soft Logic

A fundamental challenge in developing high-impact machine learning techn...
05/17/2015 ∙ by Stephen H. Bach, et al. ∙ 0 ∙ share

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Expectation Consistent Approximate Inference: Generalizations and Convergence

Approximations of loopy belief propagation, including expectation propag...
02/25/2016 ∙ by Alyson K. Fletcher, et al. ∙ 0 ∙ share

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WordRank: Learning Word Embeddings via Robust Ranking

Embedding words in a vector space has gained a lot of attention in recen...
06/09/2015 ∙ by Shihao Ji, et al. ∙ 0 ∙ share

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Bayesian Conditional Density Filtering

We propose a Conditional Density Filtering (C-DF) algorithm for efficien...
01/15/2014 ∙ by Shaan Qamar, et al. ∙ 0 ∙ share

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A Semiparametric Bayesian Extreme Value Model Using a Dirichlet Process Mixture of Gamma Densities

In this paper we propose a model with a Dirichlet process mixture of gam...
04/02/2013 ∙ by Jairo Fuquene, et al. ∙ 0 ∙ share

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Gaussian Processes and Limiting Linear Models

Gaussian processes retain the linear model either as a special case, or ...
04/29/2008 ∙ by Robert B. Gramacy, et al. ∙ 0 ∙ share

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Text Annotation Graphs: Annotating Complex Natural Language Phenomena

This paper introduces a new web-based software tool for annotating text,...
11/01/2017 ∙ by Angus G. Forbes, et al. ∙ 0 ∙ share

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Summarizing Dialogic Arguments from Social Media

Online argumentative dialog is a rich source of information on popular b...
10/31/2017 ∙ by Amita Misra, et al. ∙ 0 ∙ share

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A Dual Encoder Sequence to Sequence Model for Open-Domain Dialogue Modeling

Ever since the successful application of sequence to sequence learning f...
10/28/2017 ∙ by Sharath T. S., et al. ∙ 0 ∙ share

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Topic Based Sentiment Analysis Using Deep Learning

In this paper , we tackle Sentiment Analysis conditioned on a Topic in T...
10/28/2017 ∙ by Sharath T. S., et al. ∙ 0 ∙ share

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"How May I Help You?": Modeling Twitter Customer Service Conversations Using Fine-Grained Dialogue Acts

Given the increasing popularity of customer service dialogue on Twitter,...
09/15/2017 ∙ by Shereen Oraby, et al. ∙ 0 ∙ share

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Combining Search with Structured Data to Create a More Engaging User Experience in Open Domain Dialogue

The greatest challenges in building sophisticated open-domain conversati...
09/15/2017 ∙ by Kevin K. Bowden, et al. ∙ 0 ∙ share

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Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue

The use of irony and sarcasm in social media allows us to study them at ...
09/15/2017 ∙ by Shereen Oraby, et al. ∙ 0 ∙ share

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