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Jan 18, 2021
Computer Vision

In this work, we proposed cross-modal learning for domain adaptation in unsupervised (xMUDA) and semi-supervised (xMoSSDA) settings. To this end, we designed a two-stream, dual-head architecture and applied a cross-modal loss to the image and point-…

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
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
Strongly Correlated Electrons
Disordered Systems and Neural Networks
Machine Learning

We have provided a general approach to constructing gauge invariant autoregressive neural network wave functions for various quantum lattice models with gauge constraints or special algebraic structures. These wave functions explicitly satisfy the g…

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

We studied bi-modal variational autoencoders (VAEs) based on a product-of-experts (PoE)architecture, in particular VAEVAE as proposed by Wu and Goodman (2019) and a new model SVAE, which we derived in an axiomatic way, and represents a generalizatio…

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

We have developed a novel mechanism, FELICIA, allowing to share data more securely in order to generate synthetic data in a federated learning context. By setting up various biased data owner scenarios, we have demonstrated the potential of our mech…

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

In this work we illustrated how it is possible to improve dirbusting by leveraging Semantic Clustering. Our approach has been proven to be effective on 8 different web applications, where the clustering approach significantly improved performance in…

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 15, 2021
Machine Learning

Local Search Algorithms for Rank-Constrained Convex Optimization

We propose greedy and local search algorithms for rank-constrained convex optimization, namely solving $\underset{\mathrm{rank}(A)\leq r^*}{\min}\, R…
Jan 15, 2021
Robotics
Computers and Society
Networking and Internet Architecture

Internet of Robotic Things: Current Technologies, Applications, Cha…

Nowadays, the Internet of Things (IoT) concept is gaining more and more notoriety bringing the number of connected devices to reach the order of bill…
Jan 15, 2021
Robotics
Artificial Intelligence

Local Navigation and Docking of an Autonomous Robot Mower using Rei…

We demonstrate a successful navigation and docking control system for the John Deere Tango autonomous mower, using only a single camera as the input.…
Jan 15, 2021
Computer Vision

Blind Image Deblurring based on Kernel Mixture

Blind Image deblurring tries to estimate blurriness and a latent image out of a blurred image. This estimation, as being an ill-posed problem, requir…
Jan 15, 2021
Machine Learning

Predictive Optimization with Zero-Shot Domain Adaptation

Prediction in a new domain without any training sample, called zero-shot domain adaptation (ZSDA), is an important task in domain adaptation. While p…
Jan 15, 2021
Computer Vision

Multi-point dimensionality reduction to improve projection layout r…

In ordinary Dimensionality Reduction (DR), each data instance in an m-dimensional space (original space) is mapped to one point in a d-dimensional sp…
Jan 15, 2021
Machine Learning
Artificial Intelligence
Logic in Computer Science

LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning

While designing inductive bias in neural architectures has been widely studied, we hypothesize that transformer networks are flexible enough to learn…
Jan 15, 2021
Human-Computer Interaction
Artificial Intelligence

Player-AI Interaction: What Neural Network Games Reveal About AI as P…

The advent of artificial intelligence (AI) and machine learning (ML) bring human-AI interaction to the forefront of HCI research. This paper argues t…
Jan 15, 2021
Computer Vision
Machine Learning

APEX-Net: Automatic Plot Extractor Network

Automatic extraction of raw data from 2D line plot images is a problem of great importance having many real-world applications. Several algorithms ha…
Jan 15, 2021
Machine Learning
Information Theory

Deciding What to Learn: A Rate-Distortion Approach

Agents that learn to select optimal actions represent a prominent focus of the sequential decision-making literature. In the face of a complex enviro…
Jan 15, 2021
Computer Vision

Temporal-Relational CrossTransformers for Few-Shot Action Recognition

We propose a novel approach to few-shot action recognition, finding temporally-corresponding frame tuples between the query and videos in the support…
Jan 15, 2021
Artificial Intelligence

Hierarchical Width-Based Planning and Learning

Width-based search methods have demonstrated state-of-the-art performance in a wide range of testbeds, from classical planning problems to image-base…
Jan 15, 2021
Computer Vision

PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation

Image Segmentation plays an essential role in computer vision and image processing with various applications from medical diagnosis to autonomous car…
Jan 15, 2021
Computation and Language
Machine Learning

Empirical Evaluation of Supervision Signals for Style Transfer Models

Text style transfer has gained increasing attention from the research community over the recent years. However, the proposed approaches vary in many …
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