University of California, San Diego

research

∙ 08/05/2020

MusPy: A Toolkit for Symbolic Music Generation

In this paper, we present MusPy, an open source Python library for symbo...

Hao-Wen Dong, et al. ∙

research

∙ 08/09/2021

Efficient Hyperparameter Optimization for Differentially Private Deep Learning

Tuning the hyperparameters in the differentially private stochastic grad...

Aman Priyanshu, et al. ∙

research

∙ 06/11/2020

Deep Transfer Learning with Ridge Regression

The large amount of online data and vast array of computing resources en...

Shuai Tang, et al. ∙

research

∙ 03/24/2020

A Simple Fix for Convolutional Neural Network via Coordinate Embedding

Convolutional Neural Networks (CNN) has been widely applied in the realm...

Liliang Ren, et al. ∙

research

∙ 05/02/2019

Single Image Portrait Relighting

Lighting plays a central role in conveying the essence and depth of the ...

Tiancheng Sun, et al. ∙

research

∙ 01/21/2021

MLPF: Efficient machine-learned particle-flow reconstruction using graph neural networks

In general-purpose particle detectors, the particle flow algorithm may b...

Joosep Pata, et al. ∙

research

∙ 11/14/2019

Recent Advances in Algorithmic High-Dimensional Robust Statistics

Learning in the presence of outliers is a fundamental problem in statist...

Ilias Diakonikolas, et al. ∙

research

∙ 11/16/2019

What Will Your Child Look Like? DNA-Net: Age and Gender Aware Kin Face Synthesizer

Visual kinship recognition aims to identify blood relatives from facial ...

Pengyu Gao, et al. ∙

research

∙ 06/30/2021

Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers

Neural networks are susceptible to small transformations including 2D ro...

Spandan Madan, et al. ∙

research

∙ 09/14/2021

Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation

Natural language generation (NLG) spans a broad range of tasks, each of ...

Mingkai Deng, et al. ∙

research

∙ 12/14/2021

CEM-GD: Cross-Entropy Method with Gradient Descent Planner for Model-Based Reinforcement Learning

Current state-of-the-art model-based reinforcement learning algorithms u...

Kevin Huang, et al. ∙

research

∙ 01/03/2020

Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Plans

In this paper, we address the problem of forecasting agent trajectories ...

Nachiket Deo, et al. ∙

research

∙ 08/04/2020

Music SketchNet: Controllable Music Generation via Factorized Representations of Pitch and Rhythm

Drawing an analogy with automatic image completion systems, we propose M...

Ke Chen, et al. ∙

research

∙ 10/02/2019

A Deep Factorization of Style and Structure in Fonts

We propose a deep factorization model for typographic analysis that dise...

Akshay Srivatsan, et al. ∙

research

∙ 11/27/2019

Deep Stereo using Adaptive Thin Volume Representation with Uncertainty Awareness

We present Uncertainty-aware Cascaded Stereo Network (UCS-Net) for 3D re...

Shuo Cheng, et al. ∙

research

∙ 12/09/2019

Training Deep Neural Networks to Detect Repeatable 2D Features Using Large Amounts of 3D World Capture Data

Image space feature detection is the act of selecting points or parts of...

Alexander Mai, et al. ∙

research

∙ 06/03/2020

ExKMC: Expanding Explainable k-Means Clustering

Despite the popularity of explainable AI, there is limited work on effec...

Nave Frost, et al. ∙

research

∙ 10/09/2019

Unaligned Image-to-Sequence Transformation with Loop Consistency

We tackle the problem of modeling sequential visual phenomena. Given exa...

Siyang Wang, et al. ∙

research

∙ 08/22/2019

Adversarial-Based Knowledge Distillation for Multi-Model Ensemble and Noisy Data Refinement

Generic Image recognition is a fundamental and fairly important visual p...

Zhiqiang Shen, et al. ∙

research

∙ 05/18/2022

Constraint-Based Causal Structure Learning from Undersampled Graphs

Graphical structures estimated by causal learning algorithms from time s...

Mohammadsajad Abavisani, et al. ∙

research

∙ 01/25/2019

Faster Boosting with Smaller Memory

The two state-of-the-art implementations of boosted trees: XGBoost and L...

Julaiti Alafate, et al. ∙

research

∙ 09/02/2019

A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text

When trained effectively, the Variational Autoencoder (VAE) is both a po...

Bohan Li, et al. ∙

research

∙ 04/08/2022

An Adaptive Black-box Backdoor Detection Method for Deep Neural Networks

With the surge of Machine Learning (ML), An emerging amount of intellige...

Xinqiao Zhang, et al. ∙

research

∙ 01/29/2020

Patient Specific Biomechanics Are Clinically Significant In Accurate Computer Aided Surgical Image Guidance

Augmented Reality is used in Image Guided surgery (AR IG) to fuse surgic...

Michael Barrow, et al. ∙

research

∙ 12/27/2019

Minimax Semiparametric Learning With Approximate Sparsity

Many objects of interest can be expressed as a linear, mean square conti...

Jelena Bradic, et al. ∙

research

∙ 08/12/2021

MicroNet: Improving Image Recognition with Extremely Low FLOPs

This paper aims at addressing the problem of substantial performance deg...

Yunsheng Li, et al. ∙

research

∙ 04/07/2022

Class-Incremental Learning with Strong Pre-trained Models

Class-incremental learning (CIL) has been widely studied under the setti...

Tz-Ying Wu, et al. ∙

research

∙ 06/03/2022

KCRL: Krasovskii-Constrained Reinforcement Learning with Guaranteed Stability in Nonlinear Dynamical Systems

Learning a dynamical system requires stabilizing the unknown dynamics to...

Sahin Lale, et al. ∙

research

∙ 12/04/2018

Complete the Look: Scene-based Complementary Product Recommendation

Modeling fashion compatibility is challenging due to its complexity and ...

Wang-Cheng Kang, et al. ∙

research

∙ 02/10/2019

The Optimal Approximation Factor in Density Estimation

Consider the following problem: given two arbitrary densities q_1,q_2 an...

Olivier Bousquet, et al. ∙

research

∙ 11/30/2019

Morphing and Sampling Network for Dense Point Cloud Completion

3D point cloud completion, the task of inferring the complete geometric ...

Minghua Liu, et al. ∙

research

∙ 11/24/2019

Normal Assisted Stereo Depth Estimation

Accurate stereo depth estimation plays a critical role in various 3D tas...

Uday Kusupati, et al. ∙

research

∙ 01/15/2020

Mode-Assisted Unsupervised Learning of Restricted Boltzmann Machines

Restricted Boltzmann machines (RBMs) are a powerful class of generative ...

Haik Manukian, et al. ∙

research

∙ 11/22/2021

Image Based Reconstruction of Liquids from 2D Surface Detections

In this work, we present a solution to the challenging problem of recons...

Florian Richter, et al. ∙

research

∙ 12/16/2021

Learning Bounded Context-Free-Grammar via LSTM and the Transformer:Difference and Explanations

Long Short-Term Memory (LSTM) and Transformers are two popular neural ar...

Hui Shi, et al. ∙

research

∙ 11/05/2018

Model Extraction and Active Learning

Machine learning is being increasingly used by individuals, research ins...

Varun Chandrasekaran, et al. ∙

research

∙ 01/17/2022

Neural Computed Tomography

Motion during acquisition of a set of projections can lead to significan...

Kunal Gupta, et al. ∙

research

∙ 01/17/2019

CodeX: Bit-Flexible Encoding for Streaming-based FPGA Acceleration of DNNs

This paper proposes CodeX, an end-to-end framework that facilitates enco...

Mohammad Samragh, et al. ∙

research

∙ 11/24/2019

"Looking at the right stuff" – Guided semantic-gaze for autonomous driving

In recent years, predicting driver's focus of attention has been a very ...

Anwesan Pal, et al. ∙

research

∙ 03/04/2020

Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices

Recent advances demonstrate that irregularly wired neural networks from ...

Byung Hoon Ahn, et al. ∙

research

∙ 03/08/2020

Progressive Growing of Neural ODEs

Neural Ordinary Differential Equations (NODEs) have proven to be a power...

Hammad A. Ayyubi, et al. ∙

research

∙ 07/02/2020

The Impact of Explanations on AI Competency Prediction in VQA

Explainability is one of the key elements for building trust in AI syste...

Kamran Alipour, et al. ∙

research

∙ 11/16/2021

Polymatrix Competitive Gradient Descent

Many economic games and machine learning approaches can be cast as compe...

Jeffrey Ma, et al. ∙

research

∙ 05/05/2022

RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks

Modeling and manipulating elasto-plastic objects are essential capabilit...

Haochen Shi, et al. ∙

research

∙ 06/10/2019

Associative Convolutional Layers

Motivated by the necessity for parameter efficiency in distributed machi...

Hamed Omidvar, et al. ∙

research

∙ 02/05/2020

Continuous Melody Generation via Disentangled Short-Term Representations and Structural Conditions

Automatic music generation is an interdisciplinary research topic that c...

Ke Chen, et al. ∙

research

∙ 07/15/2020

Experimental Design for Bathymetry Editing

We describe an application of machine learning to a real-world computer ...

Julaiti Alafate, et al. ∙

research

∙ 07/20/2020

Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier

Long-tail recognition tackles the natural non-uniformly distributed data...

Tz-Ying Wu, et al. ∙

research

∙ 05/21/2022

Symmetry Teleportation for Accelerated Optimization

Existing gradient-based optimization methods update the parameters local...

Bo Zhao, et al. ∙

research

∙ 12/13/2018

SIGNet: Semantic Instance Aided Unsupervised 3D Geometry Perception

Unsupervised learning for visual perception of 3D geometry is of great i...

Yue Meng, et al. ∙

University of California, San Diego

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