b'MERL'

research

∙ 01/25/2019

Audio-Visual Scene-Aware Dialog

We introduce the task of scene-aware dialog. Given a follow-up question ...

Huda Alamri, et al. ∙

research

∙ 11/22/2019

ViewSynth: Learning Local Features from Depth using View Synthesis

We address the problem of jointly detecting keypoints and learning descr...

Jisan Mahmud, et al. ∙

research

∙ 01/22/2020

Local Policy Optimization for Trajectory-Centric Reinforcement Learning

The goal of this paper is to present a method for simultaneous trajector...

Patrik Kolaric, et al. ∙

research

∙ 03/15/2020

MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird's Eye View Maps

The ability to reliably perceive the environmental states, particularly ...

Pengxiang Wu, et al. ∙

research

∙ 02/15/2019

Street Scene: A new dataset and evaluation protocol for video anomaly detection

Progress in video anomaly detection research is currently slowed by smal...

Bharathkumar Ramachandra, et al. ∙

research

∙ 03/29/2022

Learning to Synthesize Volumetric Meshes from Vision-based Tactile Imprints

Vision-based tactile sensors typically utilize a deformable elastomer an...

Xinghao Zhu, et al. ∙

research

∙ 09/26/2019

Graph-Preserving Grid Layout: A Simple Graph Drawing Method for Graph Classification using CNNs

Graph convolutional networks (GCNs) suffer from the irregularity of grap...

Yecheng Lyu, et al. ∙

research

∙ 12/28/2021

Multi-Band Wi-Fi Sensing with Matched Feature Granularity

Complementary to the fine-grained channel state information (CSI) from t...

Jianyuan Yu, et al. ∙

research

∙ 03/21/2022

Learning robot motor skills with mixed reality

Mixed Reality (MR) has recently shown great success as an intuitive inte...

Eric Rosen, et al. ∙

research

∙ 05/06/2020

Stochastic Bottleneck: Rateless Auto-Encoder for Flexible Dimensionality Reduction

We propose a new concept of rateless auto-encoders (RL-AEs) that enable ...

Toshiaki Koike-Akino, et al. ∙

research

∙ 02/18/2022

(2.5+1)D Spatio-Temporal Scene Graphs for Video Question Answering

Spatio-temporal scene-graph approaches to video-based reasoning tasks su...

Anoop Cherian, et al. ∙

research

∙ 07/12/2018

Sem-GAN: Semantically-Consistent Image-to-Image Translation

Unpaired image-to-image translation is the problem of mapping an image i...

Anoop Cherian, et al. ∙

research

∙ 01/17/2020

Spatio-Temporal Ranked-Attention Networks for Video Captioning

Generating video descriptions automatically is a challenging task that i...

Anoop Cherian, et al. ∙

research

∙ 05/21/2018

Invariant Representations from Adversarially Censored Autoencoders

We combine conditional variational autoencoders (VAE) with adversarial c...

Ye Wang, et al. ∙

research

∙ 03/06/2019

Channel Decoding with Quantum Approximate Optimization Algorithm

Motivated by the recent advancement of quantum processors, we investigat...

Toshiki Matsumine, et al. ∙

research

∙ 03/09/2019

Deep Learning-Based Constellation Optimization for Physical Network Coding in Two-Way Relay Networks

This paper studies a new application of deep learning (DL) for optimizin...

Toshiki Matsumine, et al. ∙

research

∙ 03/09/2019

Learning to Modulate for Non-coherent MIMO

The deep learning trend has recently impacted a variety of fields, inclu...

Ye Wang, et al. ∙

research

∙ 03/09/2019

Polar Coding with Chemical Reaction Networks

In this paper, we propose a new polar coding scheme with molecular progr...

Toshiki Matsumine, et al. ∙

research

∙ 03/13/2019

Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learning

In this paper, we propose a reinforcement learning-based algorithm for t...

Kei Ota, et al. ∙

research

∙ 11/22/2019

Neural Turbo Equalization: Deep Learning for Fiber-Optic Nonlinearity Compensation

Recently, data-driven approaches motivated by modern deep learning have ...

Toshiaki Koike-Akino, et al. ∙

research

∙ 03/03/2020

Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path

In this paper, we consider the problem of building learning agents that ...

Kei Ota, et al. ∙

research

∙ 06/12/2020

Analysis of Nonlinear Fiber Interactions for Finite-Length Constant-Composition Sequences

In order to realize probabilistically shaped signaling within the probab...

Tobias Fehenberger, et al. ∙

research

∙ 06/12/2020

Huffman-coded Sphere Shaping and Distribution Matching Algorithms via Lookup Tables

In this paper, we study amplitude shaping schemes for the probabilistic ...

Tobias Fehenberger, et al. ∙

research

∙ 07/22/2020

Robust Machine Learning via Privacy/Rate-Distortion Theory

Robust machine learning formulations have emerged to address the prevale...

Ye Wang, et al. ∙

research

∙ 04/07/2022

Heterogeneous Target Speech Separation

We introduce a new paradigm for single-channel target source separation ...

Efthymios Tzinis, et al. ∙

research

∙ 11/20/2017

Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks

By lifting the ReLU function into a higher dimensional space, we develop...

Ziming Zhang, et al. ∙

research

∙ 11/19/2017

BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning

Understanding the global optimality in deep learning (DL) has been attra...

Ziming Zhang, et al. ∙

research

∙ 10/17/2017

3D Object Discovery and Modeling Using Single RGB-D Images Containing Multiple Object Instances

Unsupervised object modeling is important in robotics, especially for ha...

Wim Abbeloos, et al. ∙

research

∙ 10/31/2016

Full-Capacity Unitary Recurrent Neural Networks

Recurrent neural networks are powerful models for processing sequential ...

Scott Wisdom, et al. ∙

research

∙ 06/28/2017

Submodular Function Maximization for Group Elevator Scheduling

We propose a novel approach for group elevator scheduling by formulating...

Srikumar Ramalingam, et al. ∙

research

∙ 08/21/2017

Preconditioned Spectral Clustering for Stochastic Block Partition Streaming Graph Challenge

Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG) is demo...

David Zhuzhunashvili, et al. ∙

research

∙ 08/18/2015

Deep clustering: Discriminative embeddings for segmentation and separation

We address the problem of acoustic source separation in a deep learning ...

John R. Hershey, et al. ∙

research

∙ 09/09/2014

Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures

Model-based methods and deep neural networks have both been tremendously...

John R. Hershey, et al. ∙

research

∙ 06/13/2017

Online Convolutional Dictionary Learning for Multimodal Imaging

Computational imaging methods that can exploit multiple modalities have ...

Kevin Degraux, et al. ∙

research

∙ 05/27/2017

CASENet: Deep Category-Aware Semantic Edge Detection

Boundary and edge cues are highly beneficial in improving a wide variety...

Zhiding Yu, et al. ∙

research

∙ 05/09/2017

Signal reconstruction via operator guiding

Signal reconstruction from a sample using an orthogonal projector onto a...

Andrew Knyazev, et al. ∙

research

∙ 05/05/2017

SEAGLE: Sparsity-Driven Image Reconstruction under Multiple Scattering

Multiple scattering of an electromagnetic wave as it passes through an o...

Hsiou-Yuan Liu, et al. ∙

research

∙ 01/05/2017

Signed Laplacian for spectral clustering revisited

Classical spectral clustering is based on a spectral decomposition of a ...

Andrew V. Knyazev, et al. ∙

research

∙ 12/23/2015

Representation and Coding of Signal Geometry

Approaches to signal representation and coding theory have traditionally...

Petros T. Boufounos, et al. ∙

research

∙ 12/19/2017

FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds

Recent deep networks that directly handle points in a point set, e.g., P...

Yaoqing Yang, et al. ∙

research

∙ 12/19/2017

Neighbors Do Help: Deeply Exploiting Local Structures of Point Clouds

Unlike on images, semantic learning on 3D point clouds using a deep netw...

Yiru Shen, et al. ∙

research

∙ 12/19/2017

Privacy-Preserving Adversarial Networks

We propose a data-driven framework for optimizing privacy-preserving dat...

Ardhendu Tripathy, et al. ∙

research

∙ 02/06/2017

Attentional Network for Visual Object Detection

We propose augmenting deep neural networks with an attention mechanism f...

Kota Hara, et al. ∙

research

∙ 01/11/2017

Attention-Based Multimodal Fusion for Video Description

Currently successful methods for video description are based on encoder-...

Chiori Hori, et al. ∙

research

∙ 11/23/2016

Learning Joint Feature Adaptation for Zero-Shot Recognition

Zero-shot recognition (ZSR) aims to recognize target-domain data instanc...

Ziming Zhang, et al. ∙

research

∙ 12/15/2015

Learning optimal nonlinearities for iterative thresholding algorithms

Iterative shrinkage/thresholding algorithm (ISTA) is a well-studied meth...

Ulugbek S. Kamilov, et al. ∙

research

∙ 10/05/2016

Compressive Imaging with Iterative Forward Models

We propose a new compressive imaging method for reconstructing 2D or 3D ...

Hsiou-Yuan Liu, et al. ∙

research

∙ 06/24/2016

Coupled Generative Adversarial Networks

We propose coupled generative adversarial network (CoGAN) for learning a...

Ming-Yu Liu, et al. ∙

research

∙ 03/04/2016

Depth Superresolution using Motion Adaptive Regularization

Spatial resolution of depth sensors is often significantly lower compare...

Ulugbek S. Kamilov, et al. ∙

research

∙ 01/08/2016

Learning to Remove Multipath Distortions in Time-of-Flight Range Images for a Robotic Arm Setup

Range images captured by Time-of-Flight (ToF) cameras are corrupted with...

Kilho Son, et al. ∙

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