## An Exploration into why Output Regularization Mitigates Label Noise

Label noise presents a real challenge for supervised learning algorithms . Noise robust losses is one of the more promising approaches for dealing with label noise . But their ability to mitigate label noise lackmathematical rigor. In this work we aim at closing this gap by showing thatlosses, which incorporate an output regularization term, become symmetric .…

## Delving into Data Effectively Substitute Training for Black box Attack

Deep models have shown their vulnerability when processing adversarialsamples . As for the black-box attack, training a substitute model for adversarialattacks has attracted wide attention . Previous substitute training approaches focus on stealing the knowledge of the target model based on real training data or synthetic data .…

## DABT A Dependency aware Bug Triaging Method

The Dependency-aware Bug Triaging (DABT) leverages natural language processing and integer programming to assign bugs to developers . DABT is able to reduce the number of overdue bugs up to 12\% . It also decreases the average fixing time of the bugs by half .…

## ECLIPSE Envisioning Cloud Induced Perturbations in Solar Energy

ECLIPSE is a spatio-temporal neural network architecture that models cloud motion from sky images to predict both future segmented images and corresponding irradiance levels . It is based on the analysis of sequences of ground-taken sky images . It reduces temporal delay while generating visually realistic futures .…

## Weakly Supervised Multi task Learning for Concept based Explainability

In ML-aided decision-making tasks, the human-in-the-loop prefers high-level concept-based explanations instead of low-levelexplanations based on model features . We leverage multi-task learning to train a neural network that learns to predict a decision task based on the predictions of aprecedent explainability task .…

## Evaluating Query Languages and Systems for High Energy Physics Data

High-energy physics (HEP) physicists have found limited acceptance in the domain of data analysis . This is surprising since dataanalysis in HEP matches the SQL model well . Those offering the best possibilities in expressiveness, conciseness, and usability turn out to be the slowest and most expensive .…

## A deep learning model for gastric diffuse type adenocarcinoma classification in whole slide images

Gastric diffuse-type adenocarcinoma represents a disproportionately highpercentage of cases of gastric cancers occurring in the young . Usually it affects the body of the stomach,and presents shorter duration and worse prognosis compared with thedifferentiated (intestinal) type of adenodecarinoma . The main difficultyencountered in the differential diagnosis occurs with the diffuse type.…

## PanGu α Large scale Autoregressive Pretrained Chinese Language Models with Auto parallel Computation

Large-scale Pretrained Language Models (PLMs) have become the new paradigm for Natural Language Processing (NLP) PLMs with hundreds of billionsparameters such as GPT-3 have demonstrated strong performances on naturallanguage understanding and generation with \textit{few-shot in-context}learning . In this work, we present our practice on training large-scaleautoregressive language models named PanGu-$\alpha$ with up to 200 billionparameters .…

## TrustyAI Explainability Toolkit

Artificial intelligence (AI) is becoming increasingly more popular and can be found in workplaces and homes around the world . Regulation changes such as the GDPR mean that users have aright to understand how their data has been processed and saved .…

## MDETR Modulated Detection for End to End Multi Modal Understanding

MDETR is an end-to-end modulated detector thatdetects objects in an image conditioned on a raw text query . We use a transformer-based architecture to reason jointly over text and image by fusing the two modalities at an early stage of the model .…

## Points2Sound From mono to binaural audio using 3D point cloud scenes

Binaural sound that matches the visual counterpart is crucial to bring immersive experiences to people in augmented reality (AR) and virtual reality (VR) applications . This paper proposes Points2Sound, amulti-modal deep learning model which generates a binaural version from monoaudio using 3D point cloud scenes .…

## Resynchronized Uniformization and Definability Problems for Rational Relations

Regular synchronization languages can be used to define rational relations offinite words . We provide a systematic study of thedecidability of uniformization and definability problems for subclasses of rational relations . Werephrase known results in this setting and complete the picture by adding several new decidability and undecidability results .…

## Boolean Reasoning Based Biclustering for Shifting Pattern Extraction

Shifting patterns are interesting as they account constantfluctuations in data, i.e. they capture situations in which all the values inthe pattern move up or down for one dimension maintaining the range amplitudefor all the dimensions . The induction of shifting patterns by means of Boolean reasoning is due to theability of finding all inclusion–maximal {\delta-shifting patterns .…

## Frequency Superposition A Multi Frequency Stimulation Method in SSVEP based BCIs

The steady-state visual evoked potential (SSVEP) is one of the most widelyused modalities in brain-computer interfaces (BCIs) The existence of harmonics and the limited range of responsiverequencies in SSVEP make it challenging to further expand the number of targets presented .…

## I am Definitely Manipulated Even When I am Aware of it It s Ridiculous Dark Patterns from the End User Perspective

Online services pervasively employ manipulative designs (i.e., dark patterns) to influence users to purchase goods and subscriptions, spend more time on-site, or accept the harvesting of their personal data . We asked: are users aware of the presence of dark patterns?…

## Generative modeling of spatio temporal weather patterns with extreme event conditioning

Earth-systems data often exhibit highly irregular and complex patterns, for example caused byextreme weather events . Here, we propose a novel GAN-based approach forgenerating spatio-temporal weather patterns conditioned on detected extreme events . Our approach augments GAN generator and discriminator with an encodedextreme weather event segmentation mask .…

## Diverse Image Inpainting with Bidirectional and Autoregressive Transformers

Image inpainting is an underdetermined inverse problem, it naturally allowsdiverse contents that fill up missing or corrupted regions reasonably andrealistically . Prevalent approaches using convolutional neural networks (CNNs) suffer from limited perception fields for capturing global features . We propose BAT-Fill, an image inpaining framework with a novel bidirectionalautoregressive transformer (BAT-Fill) that models deep bidsirectional contexts for the generation of diverse contents .…

## Machine Learning based Lie Detector applied to a Collected and Annotated Dataset

Lie detection is considered a concern for everyone in their day to day life . People normally payattention to what their interlocutors are saying but also try to inspect their visual appearances, including faces, to find any signs that indicate whether the person is telling the truth or not .…

## An Algorithm to Effect Prompt Termination of Myopic Local Search on Kauffman s NK Landscape

In the NK model given by Kauffman, myopic local search involves flipping onerandomly-chosen bit of an N-bit decision string in every time step and accepting the new configuration if that has higher fitness . This algorithm consumes the full extent of computational resources allocated – given by the number of alternative configurations inspected – even though search is expected to terminate the moment there are no neighbors having higher fitness.…

## Consistency issues in Gaussian Mixture Models reduction algorithms

Many approximate GMR algorithms have been proposed in the past decades, although none of them provides optimality guarantees . We discuss the importance of the choice of the dissimilarity measure and the issue of consistency of all steps of a reduction algorithm with the chosen measure .…

## 2 5D Visual Relationship Detection

Visual 2.5D perception involves understanding the semantics and geometry of ascene through reasoning about object relationships with respect to the viewer in an environment . Unlike general VRD, 2 .5VRD isegocentric, using the camera’s viewpoint as a common reference . Unlike depth estimation, it is object-centric and not onlyfocuses on depth .…

## EigenGAN Layer Wise Eigen Learning for GANs

EigenGAN is able to unsupervisedly mine interpretable and controllable dimensions from different generator layers . The algorithm can discover controlled dimensions for high-level concepts such as pose and gender in the subspace of deep layers, as well as low-level terms such as hue and color .…

## Visformer The Vision friendly Transformer

Visformer outperforms both theTransformer-based and convolution-based models in terms of ImageNetclassification accuracy . The advantage becomes more significant when the training set is smaller . The code is available at https://://://github.com/danczs/Visformer. It is abbreviated from the `Vision-friendly Transformer’ with the same computational complexity as the Visformer architecture .…

## Towards Knowledge Graphs Validation through Weighted Knowledge Sources

The performance of applications rely on high-quality knowledge bases, a.k.a. Knowledge Graphs . To ensure their quality one important task is KnowledgeValidation, which measures the degree to which statements or triples of a Knowledge Graph (KG) are correct . We propose and implement a validation approach that computes a confidence score for everytriple and instance in a KG .…

## Represent Items by Items An Enhanced Representation of the Target Item for Recommendation

Item-based collaborative filtering (ICF) has been widely used in industrial applications such as recommender system and online advertising . In this paper, we propose an enhanced representation of the target item which distills relevant information from the co-occurrence items . With the enhanced representation, CER has strongerrepresentation power for the tail items compared to the state-of-the-art ICFmethods.…

## Bijective proofs for Eulerian numbers in types B and D

We give bijective proofs of the identity of Stembridge’s identity . We also establish abijective correspondence between even signed permutations and pairs of pairs of $w, E)$ with $([n, E), a threshold graph and$w$a degree ordering of$($n),$(w) and $(W)$ (W)) The bijectives rely on a representation ofsigned permutations as paths .…

## Text to Speech Synthesis Techniques for MIDI to Audio Synthesis

Speech synthesis and music audio generation from symbolic input differ in many aspects but share some similarities . The full MIDI-to-audio synthesis system is inferior to the sample-based or physical-modeling-based approaches, but we encourage TTS researchers to test their TTS models for this new task andimprove the performance .…

## Symplectic Transformations on Wigner Distributions and Time Frequency Signal Design

This work considers uncertainty relations on time frequency distributions from a signal processing viewpoint . A result from quantummechanics is used on Wigner distributions and marginalizable time frequencydistributions to investigate the change in variance of time and frequencyvariables . Operations on signals which leave uncertainty relations unchanged are studied .…

## Vacuum formed 3D printed electronics fabrication of thin rigid and free form interactive surfaces

Hybrid additive manufacturing techniques likethermoforming are becoming popular for prototyping freeform electronics . 3Dprinting the sheet material allows embedding conductive traces within thinlayers of the substrate, which can be vacuum-formed but remain conductive andinsulated . We characterise the behaviour of the vacuum-forming 3D printed sheet .…

## Case Study on Using Colours in Constructing Emotions by Interactive Digital Narratives

This article addresses the possibility of supporting the construction of emotions in the participants of Interactive Digital Narratives (IDN) by means of colours . The article uses goal models for expressing protostories . The core of the article consists of the case study where two colour synes-thetes wereasked to choose colours for eight emotions .…

## Speeding up Computational Morphogenesis with Online Neural Synthetic Gradients

A wide range of modern science and engineering applications are formulated as optimization problems with partial differential equations (PDEs) These PDE-constrained optimization problems are typically solved using a standard discretize-then-optimize approach . In many industry applicationsthat require high-resolution solutions, the discretized constraints can easilyhave millions or even billions of variables, making it very slow for the standard iterative optimizer to solve the exact gradients .…

## Scalable End to End RF Classification A Case Study on Undersized Dataset Regularization by Convolutional MST

Deep learning still lacks a general approach suitable for the unique nature and challenges of RF systems such as radar, signals intelligence, electronicwarfare, and communications . In this paper, we present a new DL approach based onmultistage training and demonstrate it on RF sensing signal classification .…

## What About the Precedent An Information Theoretic Analysis of Common Law

In common law, the outcome of a new case is determined mostly by precedent cases, rather than by existing statutes . Answering this question is crucial for guaranteeing fair and consistent judicial decision-making . We are the first to approach this question computationally by comparing twolongstanding jurisprudential views .…

## Causal Learning for Socially Responsible AI

There have been increasing concerns about Artificial Intelligence due to its unfathomable potential power . Researchers proposed to develop socially responsible AI (SRAI) One of these approaches is causal learning (CL) We survey state-of-the-art methods of CL for SRAI . We begin by examining the seven CL tools to enhance the social responsibility of AI .…

## The Design of the User Interfaces for Privacy Enhancements for Android

We present the design and design rationale for the user interfaces for Privacy Enhancements for Android (PE for Android) These UIs are built around core ideas that developers should explicitly declare the purpose of sensitive data is being used, and these permission-purpose pairs should be besplit by first party and third party uses .…

## A Comprehensive Attempt to Research Statement Generation

Research statement generation (RSG) task aims to summarize one’s researchachievements and help prepare a formal research statement . For this task, we construct an RSG dataset with 62 research statements and the corresponding 1,203 publications . We propose a practical RSG method which identifies arearcher’s research directions by topic modeling and clustering techniques .…

## Math Operation Embeddings for Open ended Solution Analysis and Feedback

Feedback on student answers and even during intermediate steps in solving questions is an important element in math education . Such feedback can help students correct their errors and ultimately lead toimproved learning outcomes . Most existing approaches for automated studentsolution analysis and feedback require manually constructing cognitive models and anticipating student errors for each question .…

## An Adaptive Learning based Generative Adversarial Network for One To One Voice Conversion

Voice Conversion (VC) deals with conversion of vocal style of one speaker to another speaker while keeping the linguistic contentsunchanged . VC task is performed through a three-stage pipeline consisting of speech analysis, speech feature mapping, and speech reconstruction . ALGAN-VC framework consists of some approaches to improve speech quality and voice similarity between source and target speakers .…