Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
2408.09015	AdaRank: Disagreement Based Module Rank Prediction for Low-rank Adaptation	With the rise of language and multimodal models of ever-increasing size, pretraining a general-purpose foundational model and adapting it to downstream tasks has become common practice. To this end, adaptation efficiency can be a critical bottleneck given the large model sizes, hence efficient finetuning methods such a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	481,247
2206.07483	Blind Estimation of a Doubly Selective OFDM Channel: A Deep Learning Algorithm and Theory	We provide a new generation solution to the fundamental old problem of a doubly selective fading channel estimation for orthogonal frequency division multiplexing (OFDM) systems. For systems based on OFDM, we propose a deep learning (DL)-based blind doubly selective channel estimator. This estimator does require no pil...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,756
2407.15224	PUFFLE: Balancing Privacy, Utility, and Fairness in Federated Learning	Training and deploying Machine Learning models that simultaneously adhere to principles of fairness and privacy while ensuring good utility poses a significant challenge. The interplay between these three factors of trustworthiness is frequently underestimated and remains insufficiently explored. Consequently, many eff...	false	false	false	false	true	false	true	false	false	false	false	false	true	true	false	false	false	false	475,083
2105.10585	Properties of the After Kernel	The Neural Tangent Kernel (NTK) is the wide-network limit of a kernel defined using neural networks at initialization, whose embedding is the gradient of the output of the network with respect to its parameters. We study the "after kernel", which is defined using the same embedding, except after training, for neural ne...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	236,436
1701.08190	Comparative Study Of Data Mining Query Languages	Since formulation of Inductive Database (IDB) problem, several Data Mining (DM) languages have been proposed, confirming that KDD process could be supported via inductive queries (IQ) answering. This paper reviews the existing DM languages. We are presenting important primitives of the DM language and classifying our l...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	67,421
1804.08138	Complex Network Analysis of Men Single ATP Tennis Matches	Who are the most significant players in the history of men tennis? Is the official ATP ranking system fair in evaluating players scores? Which players deserved the most contemplation looking at their match records? Which players have never faced yet and are likely to play against in the future? Those are just some of t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	95,696
2110.01812	UHP-SOT: An Unsupervised High-Performance Single Object Tracker	An unsupervised online object tracking method that exploits both foreground and background correlations is proposed and named UHP-SOT (Unsupervised High-Performance Single Object Tracker) in this work. UHP-SOT consists of three modules: 1) appearance model update, 2) background motion modeling, and 3) trajectory-based ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	258,901
2403.00886	Evaluating and Correcting Performative Effects of Decision Support Systems via Causal Domain Shift	When predicting a target variable $Y$ from features $X$, the prediction $\hat{Y}$ can be performative: an agent might act on this prediction, affecting the value of $Y$ that we eventually observe. Performative predictions are deliberately prevalent in algorithmic decision support, where a Decision Support System (DSS) ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	434,174
2109.02899	Blockchains through ontologies: the case study of the Ethereum ERC721 standard in OASIS (Extended Version)	Blockchains are gaining momentum due to the interest of industries and people in \emph{decentralized applications} (Dapps), particularly in those for trading assets through digital certificates secured on blockchain, called tokens. As a consequence, providing a clear unambiguous description of any activities carried ou...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	253,890
2109.03805	Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking	Panoptic scene understanding and tracking of dynamic agents are essential for robots and automated vehicles to navigate in urban environments. As LiDARs provide accurate illumination-independent geometric depictions of the scene, performing these tasks using LiDAR point clouds provides reliable predictions. However, ex...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	254,174
2406.16013	Database-Augmented Query Representation for Information Retrieval	Information retrieval models that aim to search for the documents relevant to the given query have shown many successes, which have been applied to diverse tasks. However, the query provided by the user is oftentimes very short, which challenges the retrievers to correctly fetch relevant documents. To tackle this, exis...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	466,962
2310.16252	Near-Optimal Pure Exploration in Matrix Games: A Generalization of Stochastic Bandits & Dueling Bandits	We study the sample complexity of identifying the pure strategy Nash equilibrium (PSNE) in a two-player zero-sum matrix game with noise. Formally, we are given a stochastic model where any learner can sample an entry $(i,j)$ of the input matrix $A\in[-1,1]^{n\times m}$ and observe $A_{i,j}+\eta$ where $\eta$ is a zero-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	402,641
1810.08187	Coded Caching for Heterogeneous Systems: An Optimization Perspective	In cache-aided networks, the server populates the cache memories at the users during low-traffic periods, in order to reduce the delivery load during peak-traffic hours. In turn, there exists a fundamental trade-off between the delivery load on the server and the cache sizes at the users. In this paper, we study this t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	110,777
2203.15867	Image Retrieval from Contextual Descriptions	The ability to integrate context, including perceptual and temporal cues, plays a pivotal role in grounding the meaning of a linguistic utterance. In order to measure to what extent current vision-and-language models master this ability, we devise a new multimodal challenge, Image Retrieval from Contextual Descriptions...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	288,569
2112.14040	Deep neural networks for solving forward and inverse problems of (2+1)-dimensional nonlinear wave equations with rational solitons	In this paper, we investigate the forward problems on the data-driven rational solitons for the (2+1)-dimensional KP-I equation and spin-nonlinear Schr\"odinger (spin-NLS) equation via the deep neural networks leaning. Moreover, the inverse problems of the (2+1)-dimensional KP-I equation and spin-NLS equation are studi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,438
1206.0555	Synergy-based Hand Pose Sensing: Reconstruction Enhancement	Low-cost sensing gloves for reconstruction posture provide measurements which are limited under several regards. They are generated through an imperfectly known model, are subject to noise, and may be less than the number of Degrees of Freedom (DoFs) of the hand. Under these conditions, direct reconstruction of the han...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	16,304
2003.00439	Differential Evolution with Individuals Redistribution for Real Parameter Single Objective Optimization	Differential Evolution (DE) is quite powerful for real parameter single objective optimization. However, the ability of extending or changing search area when falling into a local optimum is still required to be developed in DE for accommodating extremely complicated fitness landscapes with a huge number of local optim...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	166,305
1812.03304	Real-time Acceleration-continuous Path-constrained Trajectory Planning With Built-in Tradability Between Cruise and Time-optimal Motions	In this paper, a novel real-time acceleration-continuous path-constrained trajectory planning algorithm is proposed with an appealing built-in tradability mechanism between cruise motion and time-optimal motion. Different from existing approaches, the proposed approach smoothens time-optimal trajectories with bang-bang...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	115,981
1805.00713	CrisisMMD: Multimodal Twitter Datasets from Natural Disasters	During natural and man-made disasters, people use social media platforms such as Twitter to post textual and multime- dia content to report updates about injured or dead people, infrastructure damage, and missing or found people among other information types. Studies have revealed that this on- line information, if pro...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	96,494
2209.04114	An Artificial Chemistry Implementation of a Gene Regulatory Network	Gene Regulatory Networks are networks of interactions in biological organisms responsible for determining the production levels of proteins and peptides. Proteins are workers of a cell factory, and their production defines the goal of a cell and its development. Various attempts have been made to model such networks bo...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	316,689
2202.00182	Semi-supervised 3D Object Detection via Temporal Graph Neural Networks	3D object detection plays an important role in autonomous driving and other robotics applications. However, these detectors usually require training on large amounts of annotated data that is expensive and time-consuming to collect. Instead, we propose leveraging large amounts of unlabeled point cloud videos by semi-su...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	278,060
2211.12624	Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization	Recent research in robust optimization has shown an overfitting-like phenomenon in which models trained against adversarial attacks exhibit higher robustness on the training set compared to the test set. Although previous work provided theoretical explanations for this phenomenon using a robust PAC-Bayesian bound over ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	332,171
2305.07883	Towards Generalizable Medical Image Segmentation with Pixel-wise Uncertainty Estimation	Deep neural networks (DNNs) achieve promising performance in visual recognition under the independent and identically distributed (IID) hypothesis. In contrast, the IID hypothesis is not universally guaranteed in numerous real-world applications, especially in medical image analysis. Medical image segmentation is typic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	364,069
2309.02186	AniPortraitGAN: Animatable 3D Portrait Generation from 2D Image Collections	Previous animatable 3D-aware GANs for human generation have primarily focused on either the human head or full body. However, head-only videos are relatively uncommon in real life, and full body generation typically does not deal with facial expression control and still has challenges in generating high-quality results...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	389,962
1007.3622	A generalized risk approach to path inference based on hidden Markov models	Motivated by the unceasing interest in hidden Markov models (HMMs), this paper re-examines hidden path inference in these models, using primarily a risk-based framework. While the most common maximum a posteriori (MAP), or Viterbi, path estimator and the minimum error, or Posterior Decoder (PD), have long been around, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	7,086
2302.08969	Deep Reinforcement Learning for mmWave Initial Beam Alignment	We investigate the applicability of deep reinforcement learning algorithms to the adaptive initial access beam alignment problem for mmWave communications using the state-of-the-art proximal policy optimization algorithm as an example. In comparison to recent unsupervised learning based approaches developed to tackle t...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	346,249
1701.03342	A Study on Arbitrarily Varying Channels with Causal Side Information at the Encoder	In this work, we study two models of arbitrarily varying channels, when causal side information is available at the encoder in a causal manner. First, we study the arbitrarily varying channel (AVC) with input and state constraints, when the encoder has state information in a causal manner. Lower and upper bounds on the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	66,691
2211.05896	An improved method of delta summation for faster current value selection across filtered subsets of interval and temporal relational data	Aggregation in relational databases is accomplished through hashing and sorting interval data, which is computationally expensive and scales poorly as the data volumes grow. In this paper, we show how quantitative interval and time-series data in relational attributes can be represented using delta summary values rat...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	329,704
1607.07770	Approximate Policy Iteration for Budgeted Semantic Video Segmentation	This paper formulates and presents a solution to the new problem of budgeted semantic video segmentation. Given a video, the goal is to accurately assign a semantic class label to every pixel in the video within a specified time budget. Typical approaches to such labeling problems, such as Conditional Random Fields (CR...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,072
1303.3733	Adaptive Reduced-Rank MBER Linear Receive Processing for Large Multiuser MIMO Systems	In this work, we propose a novel adaptive reduced-rank strategy based on joint interpolation, decimation and filtering (JIDF) for large multiuser multiple-input multiple-output (MIMO) systems. In this scheme, a reduced-rank framework is proposed for linear receive processing and multiuser interference suppression accor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	22,948
2209.07618	Differentiable Bilevel Programming for Stackelberg Congestion Games	In a Stackelberg congestion game (SCG), a leader aims to maximize their own gain by anticipating and manipulating the equilibrium state at which the followers settle by playing a congestion game. Often formulated as bilevel programs, large-scale SCGs are well known for their intractability and complexity. Here, we atte...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	true	false	false	true	317,817
1910.10318	Winning the ICCV 2019 Learning to Drive Challenge	Autonomous driving has a significant impact on society. Predicting vehicle trajectories, specifically, angle and speed, is important for safe and comfortable driving. This work focuses on fusing inputs from camera sensors and visual map data which lead to significant improvement in performance and plays a key role in w...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	150,453
1602.06167	Deployment of 5G Networking Infrastructure with Machine Type Communication Considerations	Designing optimal strategies to deploy small cell stations is crucial to meet the quality-of-service requirements in next-generation cellular networks with constrained deployment costs. In this paper, a general deployment framework is proposed to jointly optimize the locations of backhaul aggregate nodes, small base st...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	52,335
2406.07657	OPTune: Efficient Online Preference Tuning	Reinforcement learning with human feedback~(RLHF) is critical for aligning Large Language Models (LLMs) with human preference. Compared to the widely studied offline version of RLHF, \emph{e.g.} direct preference optimization (DPO), recent works have shown that the online variants achieve even better alignment. However...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	463,144
0911.2284	A New Look at the Classical Entropy of Written English	A simple method for finding the entropy and redundancy of a reasonable long sample of English text by direct computer processing and from first principles according to Shannon theory is presented. As an example, results on the entropy of the English language have been obtained based on a total of 20.3 million character...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	4,922
1705.10480	Preliminary results on Ontology-based Open Data Publishing	Despite the current interest in Open Data publishing, a formal and comprehensive methodology supporting an organization in deciding which data to publish and carrying out precise procedures for publishing high-quality data, is still missing. In this paper we argue that the Ontology-based Data Management paradigm can pr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	74,408
2109.07563	Non-smooth Bayesian Optimization in Tuning Problems	Building surrogate models is one common approach when we attempt to learn unknown black-box functions. Bayesian optimization provides a framework which allows us to build surrogate models based on sequential samples drawn from the function and find the optimum. Tuning algorithmic parameters to optimize the performance ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	255,564
1104.1556	Benchmarking the Quality of Diffusion-Weighted Images	We present a novel method that allows for measuring the quality of diffusion-weighted MR images dependent on the image resolution and the image noise. For this purpose, we introduce a new thresholding technique so that noise and the signal can automatically be estimated from a single data set. Thus, no user interaction...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	9,921
1508.01352	Resilience of Networks Formed of Interdependent Modular Networks	Many infrastructure networks have a modular structure and are also interdependent. While significant research has explored the resilience of interdependent networks, there has been no analysis of the effects of modularity. Here we develop a theoretical framework for attacks on interdependent modular networks and suppor...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	45,784
1704.06687	Scatteract: Automated extraction of data from scatter plots	Charts are an excellent way to convey patterns and trends in data, but they do not facilitate further modeling of the data or close inspection of individual data points. We present a fully automated system for extracting the numerical values of data points from images of scatter plots. We use deep learning techniques t...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	72,204
2012.03049	Urban Heat Islands: Beating the Heat with Multi-Modal Spatial Analysis	In today's highly urbanized environment, the Urban Heat Island (UHI) phenomenon is increasingly prevalent where surface temperatures in urbanized areas are found to be much higher than surrounding rural areas. Excessive levels of heat stress leads to problems at various levels, ranging from the individual to the world....	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	209,966
1911.11214	Examining the Role of Clickbait Headlines to Engage Readers with Reliable Health-related Information	Clickbait headlines are frequently used to attract readers to read articles. Although this headline type has turned out to be a technique to engage readers with misleading items, it is still unknown whether the technique can be used to attract readers to reliable pieces. This study takes the opportunity to test its eff...	false	false	false	false	false	true	false	false	true	false	false	false	false	true	false	false	false	false	155,049
2210.11006	SimpleClick: Interactive Image Segmentation with Simple Vision Transformers	Click-based interactive image segmentation aims at extracting objects with a limited user clicking. A hierarchical backbone is the de-facto architecture for current methods. Recently, the plain, non-hierarchical Vision Transformer (ViT) has emerged as a competitive backbone for dense prediction tasks. This design allow...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	325,145
2408.09437	Hindi-BEIR : A Large Scale Retrieval Benchmark in Hindi	Given the large number of Hindi speakers worldwide, there is a pressing need for robust and efficient information retrieval systems for Hindi. Despite ongoing research, there is a lack of comprehensive benchmark for evaluating retrieval models in Hindi. To address this gap, we introduce the Hindi version of the BEIR be...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	481,438
1110.6590	New constructions of WOM codes using the Wozencraft ensemble	In this paper we give several new constructions of WOM codes. The novelty in our constructions is the use of the so called Wozencraft ensemble of linear codes. Specifically, we obtain the following results. We give an explicit construction of a two-write Write-Once-Memory (WOM for short) code that approaches capacity...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,818
1901.02029	Spectra of random networks with arbitrary degrees	We derive a message passing method for computing the spectra of locally tree-like networks and an approximation to it that allows us to compute closed-form expressions or fast numerical approximates for the spectral density of random graphs with arbitrary node degrees -- the so-called configuration model. We find the l...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	118,104
2206.02270	Estimating building energy efficiency from street view imagery, aerial imagery, and land surface temperature data	Current methods to determine the energy efficiency of buildings require on-site visits of certified energy auditors which makes the process slow, costly, and geographically incomplete. To accelerate the identification of promising retrofit targets on a large scale, we propose to estimate building energy efficiency from...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	300,821
2211.13090	TransVCL: Attention-enhanced Video Copy Localization Network with Flexible Supervision	Video copy localization aims to precisely localize all the copied segments within a pair of untrimmed videos in video retrieval applications. Previous methods typically start from frame-to-frame similarity matrix generated by cosine similarity between frame-level features of the input video pair, and then detect and re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	332,343
2402.13418	Efficiently Predicting Mutational Effect on Homologous Proteins by Evolution Encoding	Predicting protein properties is paramount for biological and medical advancements. Current protein engineering mutates on a typical protein, called the wild-type, to construct a family of homologous proteins and study their properties. Yet, existing methods easily neglect subtle mutations, failing to capture the effec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	431,231
2007.08988	Online Invariance Selection for Local Feature Descriptors	To be invariant, or not to be invariant: that is the question formulated in this work about local descriptors. A limitation of current feature descriptors is the trade-off between generalization and discriminative power: more invariance means less informative descriptors. We propose to overcome this limitation with a d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	187,805
1903.07973	Deep Eikonal Solvers	A deep learning approach to numerically approximate the solution to the Eikonal equation is introduced. The proposed method is built on the fast marching scheme which comprises of two components: a local numerical solver and an update scheme. We replace the formulaic local numerical solver with a trained neural network...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	124,746
2408.10195	SpaRP: Fast 3D Object Reconstruction and Pose Estimation from Sparse Views	Open-world 3D generation has recently attracted considerable attention. While many single-image-to-3D methods have yielded visually appealing outcomes, they often lack sufficient controllability and tend to produce hallucinated regions that may not align with users' expectations. In this paper, we explore an important ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	481,756
2403.14548	DINO-Tracker: Taming DINO for Self-Supervised Point Tracking in a Single Video	We present DINO-Tracker -- a new framework for long-term dense tracking in video. The pillar of our approach is combining test-time training on a single video, with the powerful localized semantic features learned by a pre-trained DINO-ViT model. Specifically, our framework simultaneously adopts DINO's features to fit ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,126
2205.07960	Meta AI at Arabic Hate Speech 2022: MultiTask Learning with Self-Correction for Hate Speech Classification	In this paper, we tackle the Arabic Fine-Grained Hate Speech Detection shared task and demonstrate significant improvements over reported baselines for its three subtasks. The tasks are to predict if a tweet contains (1) Offensive language; and whether it is considered (2) Hate Speech or not and if so, then predict the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	296,773
2409.13904	High-dimensional learning of narrow neural networks	Recent years have been marked with the fast-pace diversification and increasing ubiquity of machine learning applications. Yet, a firm theoretical understanding of the surprising efficiency of neural networks to learn from high-dimensional data still proves largely elusive. In this endeavour, analyses inspired by stati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	490,224
2004.13558	A Graph-constrained Changepoint Detection Approach for ECG Segmentation	Electrocardiogram (ECG) signal is the most commonly used non-invasive tool in the assessment of cardiovascular diseases. Segmentation of the ECG signal to locate its constitutive waves, in particular the R-peaks, is a key step in ECG processing and analysis. Over the years, several segmentation and QRS complex detectio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	174,588
2409.00005	Csi-LLM: A Novel Downlink Channel Prediction Method Aligned with LLM Pre-Training	Downlink channel temporal prediction is a critical technology in massive multiple-input multiple-output (MIMO) systems. However, existing methods that rely on fixed-step historical sequences significantly limit the accuracy, practicality, and scalability of channel prediction. Recent advances have shown that large lang...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	484,710
2310.17848	Boosting Data Analytics With Synthetic Volume Expansion	Synthetic data generation, a cornerstone of Generative Artificial Intelligence, promotes a paradigm shift in data science by addressing data scarcity and privacy while enabling unprecedented performance. As synthetic data becomes more prevalent, concerns emerge regarding the accuracy of statistical methods when applied...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	403,311
1909.05134	Robot Risk-Awareness by Formal Risk Reasoning and Planning	This paper proposes a formal robot motion risk reasoning framework and develops a risk-aware path planner that minimizes the proposed risk. While robots locomoting in unstructured or confined environments face a variety of risk, existing risk only focuses on collision with obstacles. Such risk is currently only address...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	145,006
2401.04821	MoSECroT: Model Stitching with Static Word Embeddings for Crosslingual Zero-shot Transfer	Transformer-based pre-trained language models (PLMs) have achieved remarkable performance in various natural language processing (NLP) tasks. However, pre-training such models can take considerable resources that are almost only available to high-resource languages. On the contrary, static word embeddings are easier to...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	420,547
2412.15687	GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations	We introduce GraphDOP, a new data-driven, end-to-end forecast system developed at the European Centre for Medium-Range Weather Forecasts (ECMWF) that is trained and initialised exclusively from Earth System observations, with no physics-based (re)analysis inputs or feedbacks. GraphDOP learns the correlations between ob...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	519,235
2102.06838	Learning Variable Impedance Control via Inverse Reinforcement Learning for Force-Related Tasks	Many manipulation tasks require robots to interact with unknown environments. In such applications, the ability to adapt the impedance according to different task phases and environment constraints is crucial for safety and performance. Although many approaches based on deep reinforcement learning (RL) and learning fro...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	219,894
1809.06488	In-Session Personalization for Talent Search	Previous efforts in recommendation of candidates for talent search followed the general pattern of receiving an initial search criteria and generating a set of candidates utilizing a pre-trained model. Traditionally, the generated recommendations are final, that is, the list of potential candidates is not modified unle...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	108,073
2011.13614	Multi-task MR Imaging with Iterative Teacher Forcing and Re-weighted Deep Learning	Noises, artifacts, and loss of information caused by the magnetic resonance (MR) reconstruction may compromise the final performance of the downstream applications. In this paper, we develop a re-weighted multi-task deep learning method to learn prior knowledge from the existing big dataset and then utilize them to ass...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	208,542
1712.08230	Block-Diagonal and LT Codes for Distributed Computing With Straggling Servers	We propose two coded schemes for the distributed computing problem of multiplying a matrix by a set of vectors. The first scheme is based on partitioning the matrix into submatrices and applying maximum distance separable (MDS) codes to each submatrix. For this scheme, we prove that up to a given number of partitions t...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	87,154
1711.08362	RGB-D-based Human Motion Recognition with Deep Learning: A Survey	Human motion recognition is one of the most important branches of human-centered research activities. In recent years, motion recognition based on RGB-D data has attracted much attention. Along with the development in artificial intelligence, deep learning techniques have gained remarkable success in computer vision. I...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,192
2011.08019	On the Effectiveness of Vision Transformers for Zero-shot Face Anti-Spoofing	The vulnerability of face recognition systems to presentation attacks has limited their application in security-critical scenarios. Automatic methods of detecting such malicious attempts are essential for the safe use of facial recognition technology. Although various methods have been suggested for detecting such atta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	206,749
2502.10410	Auto-Evaluation: A Critical Measure in Driving Improvements in Quality and Safety of AI-Generated Lesson Resources	As a publicly funded body in the UK, Oak National Academy is in a unique position to innovate within this field as we have a comprehensive curriculum of approximately 13,000 open education resources (OER) for all National Curriculum subjects, designed and quality-assured by expert, human teachers. This has provided the...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	533,857
2111.03030	Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings	Many models for undirected graphs are based on factorizing the graph's adjacency matrix; these models find a vector representation of each node such that the predicted probability of a link between two nodes increases with the similarity (dot product) of their associated vectors. Recent work has shown that these models...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	265,033
2007.00642	All in the Exponential Family: Bregman Duality in Thermodynamic Variational Inference	The recently proposed Thermodynamic Variational Objective (TVO) leverages thermodynamic integration to provide a family of variational inference objectives, which both tighten and generalize the ubiquitous Evidence Lower Bound (ELBO). However, the tightness of TVO bounds was not previously known, an expensive grid sear...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	185,169
1211.3233	New algorithm for footstep localization using seismic sensors in an indoor environment	In this study, we consider the use of seismic sensors for footstep localization in indoor environments. A popular strategy of localization is to use the measured differences in arrival times of source signals at multiple pairs of receivers. In the literature, most algorithms that are based on time differences of arriva...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	19,731
1802.05312	Learning Deep Disentangled Embeddings with the F-Statistic Loss	Deep-embedding methods aim to discover representations of a domain that make explicit the domain's class structure and thereby support few-shot learning. Disentangling methods aim to make explicit compositional or factorial structure. We combine these two active but independent lines of research and propose a new parad...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	90,410
1912.04321	Learning to Code: Coded Caching via Deep Reinforcement Learning	We consider a system comprising a file library and a network with a server and multiple users equipped with cache memories. The system operates in two phases: a prefetching phase, where users load their caches with parts of contents from the library, and a delivery phase, where users request files from the library and ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	156,810
1910.10958	Malware Classification using Deep Learning based Feature Extraction and Wrapper based Feature Selection Technique	In the case of malware analysis, categorization of malicious files is an essential part after malware detection. Numerous static and dynamic techniques have been reported so far for categorizing malware. This research presents a deep learning-based malware detection (DLMD) technique based on static methods for classify...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	150,641
2005.08035	Single-participant structural connectivity matrices lead to greater accuracy in classification of participants than function in autism in MRI	In this work, we introduce a technique of deriving symmetric connectivity matrices from regional histograms of grey-matter volume estimated from T1-weighted MRIs. We then validated the technique by inputting the connectivity matrices into a convolutional neural network (CNN) to classify between participants with autism...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	177,476
2110.09101	Vega: A 10-Core SoC for IoT End-Nodes with DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode	The Internet-of-Things requires end-nodes with ultra-low-power always-on capability for a long battery lifetime, as well as high performance, energy efficiency, and extreme flexibility to deal with complex and fast-evolving near-sensor analytics algorithms (NSAAs). We present Vega, an IoT end-node SoC capable of scalin...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	261,677
2402.09136	DolphCoder: Echo-Locating Code Large Language Models with Diverse and Multi-Objective Instruction Tuning	Code Large Language Models (Code LLMs) have demonstrated outstanding performance in code-related tasks. Several instruction tuning approaches have been proposed to boost the code generation performance of pre-trained Code LLMs. In this paper, we introduce a diverse instruction model (DolphCoder) with self-evaluating fo...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	429,385
2201.10449	An adaptive closed-loop ECoG decoder for long-term and stable bimanual control of an exoskeleton by a tetraplegic	Brain-computer interfaces (BCIs) still face many challenges to step out of laboratories to be used in real-life applications. A key one persists in the high performance control of diverse effectors for complex tasks, using chronic and safe recorders. This control must be robust over time and of high decoding performanc...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	276,999
2102.04680	Tr\"aumerAI: Dreaming Music with StyleGAN	The goal of this paper to generate a visually appealing video that responds to music with a neural network so that each frame of the video reflects the musical characteristics of the corresponding audio clip. To achieve the goal, we propose a neural music visualizer directly mapping deep music embeddings to style embed...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,188
2001.10330	Parameter Calibration in Crowd Simulation Models using Approximate Bayesian Computation	Simulation models for pedestrian crowds are a ubiquitous tool in research and industry. It is crucial that the parameters of these models are calibrated carefully and ultimately it will be of interest to compare competing models to decide which model is best suited for a particular purpose. In this contribution, I demo...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	161,792
2204.04013	Mel-spectrogram features for acoustic vehicle detection and speed estimation	The paper addresses acoustic vehicle detection and speed estimation from single sensor measurements. We predict the vehicle's pass-by instant by minimizing clipped vehicle-to-microphone distance, which is predicted from the mel-spectrogram of input audio, in a supervised learning approach. In addition, mel-spectrogram-...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	290,507
1803.00439	Synchronization and Aggregation of Nonlinear Power Systems with Consideration of Bus Network Structures	We study nonlinear power systems consisting of generators, generator buses, and non-generator buses. First, looking at a generator and its bus' variables jointly, we introduce a synchronization concept for a pair of such joint generators and buses. We show that this concept is related to graph symmetry. Next, we extend...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	91,679
2407.16166	Robust Privacy Amidst Innovation with Large Language Models Through a Critical Assessment of the Risks	This study examines integrating EHRs and NLP with large language models (LLMs) to improve healthcare data management and patient care. It focuses on using advanced models to create secure, HIPAA-compliant synthetic patient notes for biomedical research. The study used de-identified and re-identified MIMIC III datasets ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	475,485
2205.11374	Looking for a Handsome Carpenter! Debiasing GPT-3 Job Advertisements	The growing capability and availability of generative language models has enabled a wide range of new downstream tasks. Academic research has identified, quantified and mitigated biases present in language models but is rarely tailored to downstream tasks where wider impact on individuals and society can be felt. In th...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	298,113
0710.3621	Numerical removal of water-vapor effects from THz-TDS measurements	One source of disturbance in a pulsed T-ray signal is attributed to ambient water vapor. Water molecules in the gas phase selectively absorb T-rays at discrete frequencies corresponding to their molecular rotational transitions. This results in prominent resonances spread over the T-ray spectrum, and in the time domain...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	801
2109.12985	Synerise at RecSys 2021: Twitter user engagement prediction with a fast neural model	In this paper we present our 2nd place solution to ACM RecSys 2021 Challenge organized by Twitter. The challenge aims to predict user engagement for a set of tweets, offering an exceptionally large data set of 1 billion data points sampled from over four weeks of real Twitter interactions. Each data point contains mult...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	257,481
2404.07593	Diffusion posterior sampling for simulation-based inference in tall data settings	Determining which parameters of a non-linear model best describe a set of experimental data is a fundamental problem in science and it has gained much traction lately with the rise of complex large-scale simulators. The likelihood of such models is typically intractable, which is why classical MCMC methods can not be u...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	445,899
2010.16185	Optimization Algorithm-Based Approach for Modelling Large Deflection of Cantilever Beam Subjected to Tip Load	Beam mechanism and beam theory have attracted substantial attention from researchers, as they have been widely used in many fields such as compliant mechanisms and soft robots. The modeling of beam mechanisms becomes complicated due to the geometric nonlinearity that is proved to be significant with large deflection. A...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	203,990
2403.03359	RACE-SM: Reinforcement Learning Based Autonomous Control for Social On-Ramp Merging	Autonomous parallel-style on-ramp merging in human controlled traffic continues to be an existing issue for autonomous vehicle control. Existing non-learning based solutions for vehicle control rely on rules and optimization primarily. These methods have been seen to present significant challenges. Recent advancements ...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	435,157
2204.11397	Tensorial tomographic differential phase-contrast microscopy	We report Tensorial Tomographic Differential Phase-Contrast microscopy (T2DPC), a quantitative label-free tomographic imaging method for simultaneous measurement of phase and anisotropy. T2DPC extends differential phase-contrast microscopy, a quantitative phase imaging technique, to highlight the vectorial nature of li...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,128
2206.03799	Dyna-DM: Dynamic Object-aware Self-supervised Monocular Depth Maps	Self-supervised monocular depth estimation has been a subject of intense study in recent years, because of its applications in robotics and autonomous driving. Much of the recent work focuses on improving depth estimation by increasing architecture complexity. This paper shows that state-of-the-art performance can also...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	301,411
1811.10728	Optimization of Information-Seeking Dialogue Strategy for Argumentation-Based Dialogue System	Argumentation-based dialogue systems, which can handle and exchange arguments through dialogue, have been widely researched. It is required that these systems have sufficient supporting information to argue their claims rationally; however, the systems often do not have enough of such information in realistic situation...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	114,560
1803.09353	Stochastic bandits robust to adversarial corruptions	We introduce a new model of stochastic bandits with adversarial corruptions which aims to capture settings where most of the input follows a stochastic pattern but some fraction of it can be adversarially changed to trick the algorithm, e.g., click fraud, fake reviews and email spam. The goal of this model is to encour...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	93,476
2311.15582	Lightly Weighted Automatic Audio Parameter Extraction for the Quality Assessment of Consensus Auditory-Perceptual Evaluation of Voice	The Consensus Auditory-Perceptual Evaluation of Voice is a widely employed tool in clinical voice quality assessment that is significant for streaming communication among clinical professionals and benchmarking for the determination of further treatment. Currently, because the assessment relies on experienced clinician...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	410,568
1804.00968	In-depth Question classification using Convolutional Neural Networks	Convolutional neural networks for computer vision are fairly intuitive. In a typical CNN used in image classification, the first layers learn edges, and the following layers learn some filters that can identify an object. But CNNs for Natural Language Processing are not used often and are not completely intuitive. We h...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	94,154
2205.00763	Data-driven emotional body language generation for social robotics	In social robotics, endowing humanoid robots with the ability to generate bodily expressions of affect can improve human-robot interaction and collaboration, since humans attribute, and perhaps subconsciously anticipate, such traces to perceive an agent as engaging, trustworthy, and socially present. Robotic emotional ...	true	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	294,366
2206.07162	Category-Agnostic 6D Pose Estimation with Conditional Neural Processes	We present a novel meta-learning approach for 6D pose estimation on unknown objects. In contrast to ``instance-level" and ``category-level" pose estimation methods, our algorithm learns object representation in a category-agnostic way, which endows it with strong generalization capabilities across object categories. Sp...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	302,621
2205.10355	Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings	Human ratings are abstract representations of segmentation quality. To approximate human quality ratings on scarce expert data, we train surrogate quality estimation models. We evaluate on a complex multi-class segmentation problem, specifically glioma segmentation, following the BraTS annotation protocol. The training...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	297,668
2111.14447	ZeroCap: Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic	Recent text-to-image matching models apply contrastive learning to large corpora of uncurated pairs of images and sentences. While such models can provide a powerful score for matching and subsequent zero-shot tasks, they are not capable of generating caption given an image. In this work, we repurpose such models to ge...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	268,602
2012.07462	Learned Video Codec with Enriched Reconstruction for CLIC P-frame Coding	This paper proposes a learning-based video codec, specifically used for Challenge on Learned Image Compression (CLIC, CVPRWorkshop) 2020 P-frame coding. More specifically, we designed a compressor network with Refine-Net for coding residual signals and motion vectors. Also, for motion estimation, we introduced a hierar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	211,463

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