## An Energy Based Discontinuous Galerkin Method with Tame CFL Numbers for the Wave Equation

We extend and analyze the energy-based discontinuous Galerkin method for second order wave equations on staggered and structured meshes . By combiningspatial staggering with local time-stepping near boundaries, the methodovercomes the typical numerical stiffness associated with high order piecewisepolynomial approximations .…

## Additive Schwarz Methods for Convex Optimization with Backtracking

This paper presents a novel backtracking strategy for additive Schwarzmethods for general convex optimization problems as an acceleration scheme . Allowing for adaptive increasing and decreasing of the step size along the iterations, the convergence rate of an algorithm isgreatly improved .…

## Alpine Permafrost Modeling On the influence of topography driven lateral fluxes

Alpine environments are highly vulnerable and sensitive to changes in regional and global climate trends . Thawing and degradation of permafrost has numerous adverse environmental, economic, and societal impacts . The approach ismulti-dimensional, and therefore, inherently resolves fluxes along topographicgradients .…

## Causal Transformers Perform Below Chance on Recursive Nested Constructions Unlike Humans

Recursive processing is considered a hallmark of human linguistic abilities . A recent study evaluated recursive processing in recurrent neural languagemodels (RNN-LMs) and showed such models perform below chance level on embedded dependencies within nested constructions . Here, we study if state-of-the-art TransformerLMs do any better .…

## Improved Drug target Interaction Prediction with Intermolecular Graph Transformer

Intermolecular Graph Transformer (IGT) outperforms state-of-the-art approaches by 9.1% and 20.5% over the second best for bindingactivity and binding pose prediction . IGT exhibits promising drug screening ability against SARS-CoV-2 by identifying 83% activedrugs that have been validated by wet-lab experiments with near-native binding poses .…

## Can Explanations Be Useful for Calibrating Black Box Models

Aims to improve a black box model’s performance on a new domain given examples from the new domain . We show that thecalibration features transfer to some extent between tasks and shed light on how to effectively use them . We experiment with our method on two tasks, extractive questionanswering and natural language inference, covering adaptation from severalpairs of domains .…

## Robust monolithic solvers for the Stokes Darcy problem with the Darcy equation in primal form

We construct mesh-independent and parameter-robust monolithic solvers for the primal Stokes-Darcy problem . Numerical experiments demonstrate the parameters of the proposed solvers . The suggested preconditioners utilize operators in fractionalSobolev spaces . In each case, robustpreconditioners are derived using a unified theoretical framework .…

## Reverse Maximum Inner Product Search How to efficiently find users who would like to buy my item

E-commerce companies face situations where they want to promote and sell new or discounted items . The MIPS (maximum inner product search) finds the item with the highest inner product with a given query user . We propose Simpfer, a simple, fast,and exact algorithm for reverse MIPS .…

## Socially assistive robots deployment in healthcare settings a global perspective

Social robots are finding their place in societyis for healthcare-related applications . Yet, very little research has mapped the deployment of socially assistive robots in real settings . Using adocumentary research method, we were able to trace back 279 experiences of SARsdeployments in hospitals, elderly care centers, occupational health centers, private homes, and educational institutions worldwide .…

## Domain Adaptation on Semantic Segmentation with Separate Affine Transformation in Batch Normalization

In recent years, unsupervised domain adaptation (UDA) for semanticsegmentation has brought many researchers’attention . The proposed SEAT is simple, easily implemented and easy to integrate into existing adversarial learning based UDA methods . We introduce multi level adaptation by adding thelower-level features to the higher-level ones before feeding them to the discriminator, without adding extra discriminator like others.…

## Automatic Modeling of Social Concepts Evoked by Art Images as Multimodal Frames

Social concepts referring to non-physical objects are powerful tools to describe, index, and query the content of visual data . We propose the translation of recent theories about social concept representation into a software approach to represent them as multimodal frames, by integrating multisensory data .…

## Ethics lines and Machine learning a design and simulation of an Association Rules Algorithm for exploiting the data

Data mining techniques offer great opportunities for developing ethics lines . The aim of this study is to suggest a process forexploiting data generated by the data generated and collected from anethics line by extracting rules of association and applying the Apriorial algorithm .…

## TDACNN Target domain free Domain Adaptation Convolutional Neural Network for Drift Compensation in Gas Sensors

Sensor drift is a long-existing unpredictable problem that deteriorates the performance of gaseous substance recognition, calling for an antidrift domainadaptation algorithm . The main concept is that CNNs extract not only the domain-specific features of samples but alsothe domain-invariant features underlying both the source and target domains .…

## View Vertically A Hierarchical Network for Trajectory Prediction via Fourier Spectrums

Learning to understand and predict future motions or behaviors for agents is critical to various autonomous platforms, such as robot navigation, and self-driving cars . Previous methods mostly treat trajectories astime sequences, and reach great prediction performance . In this work, we try to focus on agents’ trajectories in another view, i.e.,…

## Bugs in our Pockets The Risks of Client Side Scanning

Some in industry and government now advocate a new technology to access targeted data: client-side scanning . CSS would enable on-device analysis of data in the clear . CSS by its nature createsserious security and privacy risks for all society while it can provide assistance for law enforcement is at best problematic, authors say .…

## MReD A Meta Review Dataset for Controllable Text Generation

Using existing text generation datasets for controllable text summarization, we are facing the problem of not having the domain knowledge and thus the aspects that could be controlled are limited . MReD consists of 7,089 meta-reviews and all its 45k sentences are manually annotated as one of the 9 categories, including abstract, strength, decision, etc.…

## A Flat Wall Theorem for Matching Minors in Bipartite Graphs

A major step in the graph minors theory of Robertson and Seymour is the transition from the Grid Theorem to a notion of local flatness of these areas in form of a large flat wall within any huge grid of anH-minor free graph .…

## Omni Training for Data Efficient Deep Learning

A properlypre-trained model endows an important property: transferability . A highertransferability of the learned representations indicates a bettergeneralizability across domains of different distributions . Transferability has become the key to enable data-efficient deep learning, however, existing pre-training methods focus only on the domaintransferability .…

## Fusing Heterogeneous Factors with Triaffine Mechanism for Nested Named Entity Recognition

Nested entities are observed in many domains due to their compositionality, which cannot be easily recognized by the widely-used sequence labelingframework . A natural solution is to treat the task as a span classificationproblem . To increase performance on span representation and classification, it is crucial to effectively integrate all useful information of differentformats .…

## Detecting Renewal States in Chains of Variable Length via Intrinsic Bayes Factors

Markov chains with variable length are useful parsimonious stochastic modelsable to generate most stationary sequence of discrete symbols . The idea is to identify suffixes of the past, called contexts, that are relevant topredict the future symbol . Sometimes a single state is a context, and lookingat the past and finding this specific state makes the further past irrelevant .…

## Provably Efficient Multi Agent Reinforcement Learning with Fully Decentralized Communication

Distributed exploration reduces samplingcomplexity in multi-agent RL (MARL) We investigate the benefits to performance in MARL when exploration is fully decentralized . We show that incorporating more agents and more information sharing into the group learning scheme speeds up convergence to the optimal policy .…

## zk Fabric a Polylithic Syntax Zero Knowledge Joint Proof System

zk-Fabric based on partitioned garbled circuits has theadvantage of being versatile and single-use, meaning it can be applied toarbitrary circuits with more comprehensive statements . It can achieve thenon-interactivity among all participants . We also designed a joint zero knowledge proof protocol that uses partitionedgarbled circuits to match thecomprehensive Boolean logical expression with multiple variables, we use the term “polythitic syntax” to refer to the context-based multiple variables in a statement .…

## Drone technology interdisciplinary systematic assessment of knowledge gaps and potential solutions

Despite being a hot research topic for a decade, drones are still not part of our everyday life . We analyze the reasons for this state ofaffairs and look for ways of improving the situation . We suggest project implementation guidelines for several drone applications .…

## Adversarial examples by perturbing high level features in intermediate decoder layers

Instead ofperturbing pixels, we use an encoder-decoder representation of the input image and perturb intermediate layers in the decoder . This changes the high-levelfeatures provided by the generative model . We formulatethis task as an optimization problem by minimizing the Wasserstein distancebetween the adversarial and initial images under a misclassificationconstraint .…

## Sparks Inspiration for Science Writing using Language Models

Large-scale language models are rapidly improving, performing well on a wide variety of tasks with little to no customization . In this work we investigate how language models can support science writing . We present a system forgenerating “sparks”, sentences related to a scientific concept intended to inspire writers .…

## Plug Tagger A Pluggable Sequence Labeling Framework Using Language Models

Plug-and-play functionality allows deep learning models to adapt well to different tasks without requiring any parameters modified . In this work, we propose the use of label word prediction instead of classification to totally reuse the architecture of pre-trained models for sequence labeling tasks .…

## Presenting a Larger Up to date Movie Dataset and Investigating the Effects of Pre released Attributes on Gross Revenue

Movie-making has become one of the most costly and risky endeavors in the entertainment industry . Researchers have been working on finding an optimal strategy to help investors in making the right decisions . We introduce an up-to-date, richer, and larger dataset that we have prepared by scraping IMDb for researchers and data analysts to work with .…

## Solving Aspect Category Sentiment Analysis as a Text Generation Task

We consider casting the ACSAtasks into natural language generation tasks, using natural language sentencesto represent the output . Our method allows more direct use of pre-trained knowledge in seq2seq language models by directly following the task setting during pre-training . Experiments on several benchmarks show that our methodgives the best reported results, having large advantages in few-shot and zero-shot settings .…