University of California Santa Cruz

research

∙ 10/02/2019

Using Image Priors to Improve Scene Understanding

Semantic segmentation algorithms that can robustly segment objects acros...

Brigit Schroeder, et al. ∙

research

∙ 10/04/2018

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

Consider linear regression where the examples are generated by an unknow...

Michal Derezinski, et al. ∙

research

∙ 01/16/2020

Estimating Aggregate Properties In Relational Networks With Unobserved Data

Aggregate network properties such as cluster cohesion and the number of ...

Varun Embar, et al. ∙

research

∙ 10/15/2021

Jurassic is (almost) All You Need: Few-Shot Meaning-to-Text Generation for Open-Domain Dialogue

One challenge with open-domain dialogue systems is the need to produce h...

Lena Reed, et al. ∙

research

∙ 06/15/2022

A Simple Data Mixing Prior for Improving Self-Supervised Learning

Data mixing (e.g., Mixup, Cutmix, ResizeMix) is an essential component f...

Sucheng Ren, et al. ∙

research

∙ 09/10/2021

D-REX: Dialogue Relation Extraction with Explanations

Existing research studies on cross-sentence relation extraction in long-...

Alon Albalak, et al. ∙

research

∙ 09/15/2021

Attention Is Indeed All You Need: Semantically Attention-Guided Decoding for Data-to-Text NLG

Ever since neural models were adopted in data-to-text language generatio...

Juraj Juraska, et al. ∙

research

∙ 05/10/2020

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

The last decade saw the emergence of systematic large-scale replication ...

Yang Liu, et al. ∙

research

∙ 11/11/2021

AlphaGarden: Learning to Autonomously Tend a Polyculture Garden

This paper presents AlphaGarden: an autonomous polyculture garden that p...

Mark Presten, et al. ∙

research

∙ 07/21/2020

Incentives for Federated Learning: a Hypothesis Elicitation Approach

Federated learning provides a promising paradigm for collecting machine ...

Yang Liu, et al. ∙

research

∙ 10/21/2021

Modeling Performance in Open-Domain Dialogue with PARADISE

There has recently been an explosion of work on spoken dialogue systems,...

Marilyn Walker, et al. ∙

research

∙ 11/03/2021

Athena 2.0: Contextualized Dialogue Management for an Alexa Prize SocialBot

Athena 2.0 is an Alexa Prize SocialBot that has been a finalist in the l...

Juraj Juraska, et al. ∙

research

∙ 08/04/2019

Hopfield Neural Network Flow: A Geometric Viewpoint

We provide gradient flow interpretations for the continuous-time continu...

Abhishek Halder, et al. ∙

research

∙ 08/27/2019

Private Stochastic Convex Optimization with Optimal Rates

We study differentially private (DP) algorithms for stochastic convex op...

Raef Bassily, et al. ∙

research

∙ 05/07/2020

A Gaussian Process Upsampling Model for Improvements in Optical Character Recognition

Optical Character Recognition and extraction is a key tool in the automa...

Steven I Reeves, et al. ∙

research

∙ 10/02/2018

Reinforcement Learning with Perturbed Rewards

Recent studies have shown the vulnerability of reinforcement learning (R...

Jingkang Wang, et al. ∙

research

∙ 01/05/2020

User Profiling Using Hinge-loss Markov Random Fields

A variety of approaches have been proposed to automatically infer the pr...

Golnoosh Farnadi, et al. ∙

research

∙ 05/13/2020

Structured Query-Based Image Retrieval Using Scene Graphs

A structured query can capture the complexity of object interactions (e....

Brigit Schroeder, et al. ∙

research

∙ 03/24/2022

Compositional Temporal Grounding with Structured Variational Cross-Graph Correspondence Learning

Temporal grounding in videos aims to localize one target video segment t...

Juncheng Li, et al. ∙

research

∙ 03/26/2020

Obliviousness Makes Poisoning Adversaries Weaker

Poisoning attacks have emerged as a significant security threat to machi...

Sanjam Garg, et al. ∙

research

∙ 07/03/2018

Scalable Structure Learning for Probabilistic Soft Logic

Statistical relational frameworks such as Markov logic networks and prob...

Varun Embar, et al. ∙

research

∙ 11/29/2018

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

Sensitive statistics are often collected across sets of users, with repe...

Úlfar Erlingsson, et al. ∙

research

∙ 07/08/2019

Unbiased estimators for random design regression

In linear regression we wish to estimate the optimum linear least square...

Michał Dereziński, et al. ∙

research

∙ 09/12/2021

"Let Your Characters Tell Their Story": A Dataset for Character-Centric Narrative Understanding

When reading a literary piece, readers often make inferences about vario...

Faeze Brahman, et al. ∙

research

∙ 04/18/2022

Imagination-Augmented Natural Language Understanding

Human brains integrate linguistic and perceptual information simultaneou...

Yujie Lu, et al. ∙

research

∙ 08/10/2022

Controlling Perceived Emotion in Symbolic Music Generation with Monte Carlo Tree Search

This paper presents a new approach for controlling emotion in symbolic m...

Lucas N. Ferreira, et al. ∙

research

∙ 01/20/2022

Classic Graph Structural Features Outperform Factorization-Based Graph Embedding Methods on Community Labeling

Graph representation learning (also called graph embeddings) is a popula...

Andrew Stolman, et al. ∙

research

∙ 02/15/2017

Time-Invariant LDPC Convolutional Codes

Spatially coupled codes have been shown to universally achieve the capac...

Dimitris Achlioptas, et al. ∙

research

∙ 11/02/2017

Dynamic Influence Networks for Rule-based Models

We introduce the Dynamic Influence Network (DIN), a novel visual analyti...

Angus G. Forbes, et al. ∙

research

∙ 12/04/2017

Learning User Intent from Action Sequences on Interactive Systems

Interactive systems have taken over the web and mobile space with increa...

Rakshit Agrawal, et al. ∙

research

∙ 11/16/2017

Using Noisy Extractions to Discover Causal Knowledge

Knowledge bases (KB) constructed through information extraction from tex...

Dhanya Sridhar, et al. ∙

research

∙ 08/29/2017

Modelling Protagonist Goals and Desires in First-Person Narrative

Many genres of natural language text are narratively structured, a testa...

Elahe Rahimtoroghi, et al. ∙

research

∙ 08/30/2017

Inference of Fine-Grained Event Causality from Blogs and Films

Human understanding of narrative is mainly driven by reasoning about cau...

Zhichao Hu, et al. ∙

research

∙ 08/30/2017

Learning Fine-Grained Knowledge about Contingent Relations between Everyday Events

Much of the user-generated content on social media is provided by ordina...

Elahe Rahimtoroghi, et al. ∙

research

∙ 07/12/2017

Automatic Mapping of NES Games with Mappy

Game maps are useful for human players, general-game-playing agents, and...

Joseph C. Osborn, et al. ∙

research

∙ 07/12/2017

Mechanics Automatically Recognized via Interactive Observation: Jumping

Jumping has been an important mechanic since its introduction in Donkey ...

Adam Summerville, et al. ∙

research

∙ 07/11/2017

CHARDA: Causal Hybrid Automata Recovery via Dynamic Analysis

We propose and evaluate a new technique for learning hybrid automata aut...

Adam Summerville, et al. ∙

research

∙ 07/11/2017

Automated Game Design Learning

While general game playing is an active field of research, the learning ...

Joseph C. Osborn, et al. ∙

research

∙ 03/02/2016

Super Mario as a String: Platformer Level Generation Via LSTMs

The procedural generation of video game levels has existed for at least ...

Adam Summerville, et al. ∙

research

∙ 02/14/2016

Surprising properties of dropout in deep networks

We analyze dropout in deep networks with rectified linear units and the ...

David P. Helmbold, et al. ∙

research

∙ 05/18/2017

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

By utilizing different communication channels, such as verbal language, ...

Kevin K. Bowden, et al. ∙

research

∙ 11/21/2015

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

We propose BlackOut, an approximation algorithm to efficiently train mas...

Shihao Ji, et al. ∙

research

∙ 02/02/2017

Procedural Content Generation via Machine Learning (PCGML)

This survey explores Procedural Content Generation via Machine Learning ...

Adam Summerville, et al. ∙

research

∙ 05/19/2017

Two-temperature logistic regression based on the Tsallis divergence

We develop a variant of multiclass logistic regression that achieves thr...

Ehsan Amid, et al. ∙

research

∙ 12/15/2014

On the Inductive Bias of Dropout

Dropout is a simple but effective technique for learning in neural netwo...

David P. Helmbold, et al. ∙

research

∙ 11/30/2016

Low-dimensional Data Embedding via Robust Ranking

We describe a new method called t-ETE for finding a low-dimensional embe...

Ehsan Amid, et al. ∙

research

∙ 11/21/2016

Learning From Graph Neighborhoods Using LSTMs

Many prediction problems can be phrased as inferences over local neighbo...

Rakshit Agrawal, et al. ∙

research

∙ 01/11/2017

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-...

Tracy Holsclaw, et al. ∙

research

∙ 04/03/2017

Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

We introduce an algorithm for word-level text spotting that is able to a...

Siyang Qin, et al. ∙

research

∙ 05/17/2015

Hinge-Loss Markov Random Fields and Probabilistic Soft Logic

A fundamental challenge in developing high-impact machine learning techn...

Stephen H. Bach, et al. ∙

University of California Santa Cruz

Featured Researchers