Rethinking Point Cloud Filtering A Non Local Position Based Approach

Existing position based point cloud filtering methods can hardly preservesharp geometric features . We propose a novel positionbased approach for feature-preserving point cloud filter . Unlike normalbased techniques, our method does not require the normal information . The coreidea is to first design a similarity metric to search the non-local similarpatches of a queried local patch .…

Quantum Rényi divergences and the strong converse exponent of state discrimination in operator algebras

The sandwiched R\’enyi divergences of two finite-dimensional quantumstates play a distinguished role among the many quantum versions of R\’enidivergences . They are tight quantifiers of the trade-off between the two errorprobabilities in the strong converse domain of state discrimination . We show the same for the sandwiched divergence of two normalstates on an injective von Neumann algebra, thereby establishing theoperational significance of these quantities .…

DeepSSM A Blueprint for Image to Shape Deep Learning Models

Statistical shape modeling (SSM) characterizes anatomical variations in apopulation of shapes generated from medical images . SSM requires consistentshape representation across samples in shape cohort . Theseshape representations are then used to extract low-dimensional shapedescriptors that facilitate subsequent analyses in different applications .…

Retrieval guided Counterfactual Generation for QA

Deep NLP models have been shown to learn spurious correlations, leaving them brittle to input perturbations . We develop a Retrieve-Generate-Filter-Filter technique to create counterfactualevaluation and training data with minimal human supervision . Using anopen-domain QA framework and question generation model trained on original task data, we create counterfactsuals that are fluent, semantically diverse, andautomatically labeled.…

Possibilistic Fuzzy Local Information C Means with Automated Feature Selection for Seafloor Segmentation

The Possibilistic Fuzzy Local Information C-Means (PFLICM) method is presented as a technique to segment side-look synthetic aperture sonar (SAS)imagery into distinct regions of the sea-floor . The chosen features and resulting segmentation from the image will be assessed based on a select quantitative clustering validitycriterion and a subset of the features that reach a desired threshold will be used for the segmentation process .…

Transferring Semantic Knowledge Into Language Encoders

We introduce semantic form mid-tuning, an approach for transferring semanticknowledge from semantic meaning representations into transformer-based languageencoders . We learn to align the text of general sentences with structured semantic representations of those sentences . We show that this alignment can be learnedimplicitly via classification or directly via triplet loss .…

A more direct and better variant of New Q Newton s method Backtracking for m equations in m variables

In this paper we propose a variant of New Q-Newton’s method Backtracking . The update rule of our method is $x\mapsto x-\gamma (x)w(x)$. Good theoretical guarantees are proven, in particular for systems ofpolynomial equations . In “generic situations”, we will also discuss a way to avoid that the limit of the constructed sequence is a solution of $H(x), but not of $F(x)=0$ The limit is a .…

Spoken ObjectNet A Bias Controlled Spoken Caption Dataset

Modern audio-visual datasets contain biases that undermine the real-world performance of models trained on that data . We introduce Spoken ObjectNet to remove some of these biases . This dataset expands upon ObjectNet, which is a bias-controlled image dataset . We detail our datacollection pipeline, which features several methods to improve caption quality, including automated language model checks .…

P Adapters Robustly Extracting Factual Information from Language Models with Diverse Prompts

P-Adapters are lightweight models that sit between the embedding layer and first attention layer of Large Language Models . They take LLM embeddings as input and output continuous prompts that are used to query the LLM . They showbetween 12-26% absolute improvement in precision and 36-50% absoluteimprovement in consistency over a baseline of only using natural languagequeries .…

A Dual Attention Neural Network for Pun Location and Using Pun Gloss Pairs for Interpretation

Pun location is to identify the punning word (usually a word or phrase that makes the text ambiguous) in a given short text . Pun interpretation is to find out two different meanings of the word . DANN (Dual-Attentive Neural Network) is proposed for pun location, effectively integrates word senses and pronunciation with context information to address two kinds of pun at the same time .…

Toward Degradation Robust Voice Conversion

Any-to-any voice conversion technologies convert the vocal timbre of anutterance to any speaker even unseen during training . But in real-world scenarios, it is difficult to collect clean utterances of a speaker, and they are usually degraded by noises or reverberations .…

On the Pitfalls of Analyzing Individual Neurons in Language Models

Many studies have shown that linguistic information is encoded inhidden word representations . Few have studied individual neurons to show how and in which neurons it is encoded . The common approach is to use an external probe to rank neurons according to their relevance to somelinguistic attribute, and to evaluate the obtained ranking using the same probethat produced it .…

RGB D Image Inpainting Using Generative Adversarial Network with a Late Fusion Approach

Diminished reality is a technology that aims to remove objects from video images and fills in the missing region with plausible pixels . We propose an RGB-D image inpainting method using generative adversarialnetwork, which does not require multiple cameras . The experimental results verify the effectiveness of our proposed method, we propose late fusion approach that exploits the advantage of RGB and depth information each other to jointly restore texture and geometry of missing regions from a pair ofRGB and depth images .…

IB GAN A Unified Approach for Multivariate Time Series Classification under Class Imbalance

Imputation Balanced GAN (IB-GAN) is anovel method that joins data augmentation and classification in a one-stepprocess via an imputation-balancing approach . IB-GAN uses imputation andresampling techniques to generate higher quality samples from randomly maskedvectors than from white noise . It augments classification through aclass-balanced set of real and synthetic samples .…

Towards a fully RL based Market Simulator

Two families of RL-based agents learn simultaneously to satisfy their objective . Each group learns a shared policy able to generalize andpolate over a wide range of behaviors . This is a step towards a fullyRL-based market simulator replicating complex market conditions, particularly suited to study the dynamics of the financial market under various scenarios .…

Order Constraints in Optimal Transport

Recent works have aimed toimprove optimal transport plans through the introduction of various forms of structure . We introduce novel order constraints into the optimal transportformulation to allow for structure . While there will are now quadratically many constraints as before, we prove a .roximatesolution…

Root Finding With Interval Arithmetic

We consider the solution of nonlinear equations in one real variable, the problem usually called by root finding . We argue that problems with just one variable are much simpler than problems with more variables . We provide animplementation of our ideas in C++, and make this code available under theMozilla Public License 2.0 .…

LAGr Labeling Aligned Graphs for Improving Systematic Generalization in Semantic Parsing

LAGr produces semantic parses by predicting node and edge labels for a complete multi-layer input-aligned graph . Thestrongly-supervised algorithm requires aligned graphs as inputs and infers alignments for originally unaligned target graphs using an approximate MAP inference procedure . On the COGS and CFQ compositionalgeneralization benchmarks the strongly- and weakly- supervised LAGR algorithmsachieve significant improvements upon the baseline seq2seq parsers.…

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 .…

Few shot Controllable Style Transfer for Low Resource Settings A Study in Indian Languages

Style transfer is the task of rewriting an input sentence into a target style while approximately preserving its content . We find existing few-shot methods perform this task poorly, with a strong tendency to copy inputs verbatim . We report promising qualitative results for several attributetransfer directions, including sentiment transfer, text simplification, genderneutralization and text anonymization, all without retraining the model .…

Dynamic Conflict Resolution of IoT Services in Smart Homes

We propose a novel conflict resolution framework for IoT services in multi-resident smart homes . The proposed framework employs a preferenceextraction model based on a temporal proximity strategy . We design a preferenceaggregation model using a matrix factorization-based approach . The concepts of current resident item matrix and idealresident item matrix are introduced as key criteria to cater to the conflictresolution framework .…

An algorithm for a fairer and better voting system

The major finding, of this article, is an ensemble method that aims to solve the problem of finding the best candidate to represent the voters . We have convincing evidence that our algorithm is better than Instant-RunoffVoting, Preferential Block Voting, Single Transferable Vote, and First Past ThePost .…

Stability and Efficiency of Random Serial Dictatorship

This paper establishes non-asymptotic convergence of the cutoffs in Randomserial dictatorship in an environment with many students, many schools, andarbitrary student preferences . Convergence is shown to hold when the number ofschools, $m$ and number of students, $n$, satisfy the relation $m \ln m\ll n$, and we provide an example showing that this result is sharp .…

The algebra of row monomial matrices

The class of row monomial matrices is closed under multiplication, but not under ordinary matrix addition . The most significant difference is the summation operation . The algebra plays an important role in the study of DFA,especially for synchronizing automata .…

Provably accurate simulation of gauge theories and bosonic systems

Quantum many-body systems involving bosonic modes or gauge fields haveinfinite-dimensional local Hilbert spaces which must be truncated to perform simulations of real-time dynamics on classical or quantum computers . We show that if states in these models aretruncated by imposing an upper limit on each local quantum number,and if the initial state has low local quantum numbers, then an error at most$\epsilon$ can be achieved by choosing $Lambda$ to scale polylogarithmically with $E-Eigenstates .…

Online Bipartite Matching with Reusable Resources

We study the classic online bipartite matching problem with a twist: offlinenodes are reusable any number of times . Every offline node $i$ becomesavailable $d$ steps after it was assigned to. We give the first approximation factor beating$0.5$ namely a $0.505$ approximation, by adapting and interpreting the powerful technique of Online Correlated Selection .…

State of Security and Privacy Practices of Top Websites in the East African Community EAC

Growth in technology has resulted in the large-scale collection and processing of Personally Identifiable Information by organizations that rundigital services such as websites . Several African countries have recently started enacting new dataprotection regulations due to recent technological innovations . Only 16 percent of third-party tracking companies that track users on a particular website are disclosed in the site’s privacy policy statements .…

SAR Net A Scenario Aware Ranking Network for PersonalizedFair Recommendation in Hundreds of Travel Scenarios

Alibaba serves an indispensable role forhundreds of different travel scenarios from Fliggy, Taobao, Alipay apps, etc. To provide personalized recommendation service for users visiting differentscenarios, there are two critical issues to be carefully addressed . In this paper, we propose a novelScenario-Aware Ranking Network (SAR-Net) to address these issues .…