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Jan 18, 2021
Computer Vision

Cross-modal Learning for Domain Adaptation in 3D Semantic Segmentation

Domain adaptation is an important task to enable learning when labels are scarce. While most works focus only on the image modality, there are many i…
Jan 18, 2021
Strongly Correlated Electrons
Disordered Systems and Neural Networks
Machine Learning

Gauge Invariant Autoregressive Neural Networks for Quantum Lattice …

Gauge invariance plays a crucial role in quantum mechanics from condensed matter physics to high energy physics. We develop an approach to constructi…
Jan 18, 2021
Machine Learning
Artificial Intelligence

Multimodal Variational Autoencoders for Semi-Supervised Learning: In …

Multimodal generative models should be able to learn a meaningful latent representation that enables a coherent joint generation of all modalities (e…
Jan 18, 2021
Machine Learning
Artificial Intelligence
Computer Vision
Distributed
Parallel
and Cluster Computing

Reducing bias and increasing utility by federated generative modeling…

We introduce FELICIA (FEderated LearnIng with a CentralIzed Adversary) a generative mechanism enabling collaborative learning. In particular, we show…
Jan 18, 2021
Cryptography and Security
Artificial Intelligence
Machine Learning

Leveraging AI to optimize website structure discovery during Penetrat…

Dirbusting is a technique used to brute force directories and file names on web servers while monitoring HTTP responses, in order to enumerate server…
Jan 18, 2021
Computer Vision
Machine Learning

Assisting Barrett's esophagus identification using endoscopic data …

Computer-aided approaches for automatic diagnosis emerged in the literature since early detection is intrinsically related to remission probabilities…
Jan 18, 2021
Machine Learning
Systems and Control

Quantification of Disaggregation Difficulty with Respect to the Numbe…

A promising approach toward efficient energy management is non-intrusive load monitoring (NILM), that is to extract the consumption profiles of appli…
Jan 18, 2021
Machine Learning
Systems and Control

Incorporating Coincidental Water Data into Non-intrusive Load Monitor…

Non-intrusive load monitoring (NILM) as the process of extracting the usage pattern of appliances from the aggregated power signal is among successfu…
Jan 18, 2021
Robotics
Machine Learning
Systems and Control

Deep Reinforcement Learning with Embedded LQR Controllers

Reinforcement learning is a model-free optimal control method that optimizes a control policy through direct interaction with the environment. For re…
Jan 18, 2021
Computer Vision

HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Netw…

We propose a new convolution neural network called HarDNet-MSEG for polyp segmentation. It achieves SOTA in both accuracy and inference speed on five…
Jan 18, 2021
Robotics

Generation of GelSight Tactile Images for Sim2Real Learning

Most current works in Sim2Real learning for robotic manipulation tasks leverage camera vision that may be significantly occluded by robot hands durin…
Jan 18, 2021
Social and Information Networks
Data Structures and Algorithms
Machine Learning

PRESTO: Simple and Scalable Sampling Techniques for the Rigorous Ap…

The identification and counting of small graph patterns, called network motifs, is a fundamental primitive in the analysis of networks, with applicat…
Jan 18, 2021
Machine Learning

Stable Recovery of Entangled Weights: Towards Robust Identification o…

In this paper we approach the problem of unique and stable identifiability of generic deep artificial neural networks with pyramidal shape and smooth…
Jan 18, 2021
Machine Learning
Artificial Intelligence
Computation and Language
Robotics

Interpretable Policy Specification and Synthesis through Natural La…

Policy specification is a process by which a human can initialize a robot's behaviour and, in turn, warm-start policy optimization via Reinforcement …
Jan 18, 2021
Machine Learning

This paper presented a model to carry out classification of an open-access fNIRS dataset, while taking uncertainty into consideration. The dataset consisted of unilateral right and left finger tapping. We used a Bayesian Neural Network model to clas…

Classification of fNIRS Data Under Uncertainty: A Bayesian Neural N…

Functional Near-Infrared Spectroscopy (fNIRS) is a non-invasive form of Brain-Computer Interface (BCI). It is used for the imaging of brain hemodynam…
Jan 18, 2021
Machine Learning

A simple geometric proof for the benefit of depth in ReLU networks

We present a simple proof for the benefit of depth in multi-layer feedforward network with rectified activation ("depth separation"). Specifically we…
Jan 18, 2021
Information Retrieval
Human-Computer Interaction

Tip of the Tongue Known-Item Retrieval: A Case Study in Movie Ident…

While current information retrieval systems are effective for known-item retrieval where the searcher provides a precise name or identifier for the i…
Jan 18, 2021
Machine Learning
Artificial Intelligence
Multiagent Systems
Trading and Market Microstructure

Deep Reinforcement Learning for Active High Frequency Trading

We introduce the first end-to-end Deep Reinforcement Learning based framework for active high frequency trading. We train DRL agents to to trade one …
Jan 18, 2021
Machine Learning
Social and Information Networks

In this paper, we proposed a method to force alignment as well as a measuring procedure able to describe the alignment and stability of dynamic network embeddings. In order to demonstrate the validity of the developed measures, we conducted differen…

Alignment and stability of embeddings: measurement and inference im…

Representation learning (RL) methods learn objects' latent embeddings where information is preserved by distances. Since distances are invariant to c…
Jan 18, 2021
Computer Vision

Deep Universal Blind Image Denoising

Image denoising is an essential part of many image processing and computer vision tasks due to inevitable noise corruption during image acquisition. …
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