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
2006.05071	C-SL: Contrastive Sound Localization with Inertial-Acoustic Sensors	Human brain employs perceptual information about the head and eye movements to update the spatial relationship between the individual and the surrounding environment. Based on this cognitive process known as spatial updating, we introduce contrastive sound localization (C-SL) with mobile inertial-acoustic sensor arrays...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	180,926
2212.11522	AsyncFLEO: Asynchronous Federated Learning for LEO Satellite Constellations with High-Altitude Platforms	Low Earth Orbit (LEO) constellations, each comprising a large number of satellites, have become a new source of big data "from the sky". Downloading such data to a ground station (GS) for big data analytics demands very high bandwidth and involves large propagation delays. Federated Learning (FL) offers a promising sol...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	337,819
2108.02753	Safe Motion Planning against Multimodal Distributions based on a Scenario Approach	We present the design of a motion planning algorithm that ensures safety for an autonomous vehicle. In particular, we consider a multimodal distribution over uncertainties; for example, the uncertain predictions of future trajectories of surrounding vehicles reflect discrete decisions, such as turning or going straight...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	249,434
2406.16408	A Symmetry Property of Christoffel Words	Motivated by the theory of trapezoidal words, whose sequences of cardinality of factors by length are symmetric, we introduce a bivariate variant of this symmetry. We show that this symmetry characterizes Christoffel words, and establish other related results.	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	467,119
2104.07630	Otaku: Intelligent Management System for Student-Intensive Dormitory	In most student dorms in developing countries, a large number of people live in single-function dorm units. The division of the dormitory is too fixed, resulting in the dormitory often lacking functional spaces such as entertainment, sports, meetings, etc. At the same time, a large number of people are likely to cause ...	false	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	230,487
2410.17785	TranSPORTmer: A Holistic Approach to Trajectory Understanding in Multi-Agent Sports	Understanding trajectories in multi-agent scenarios requires addressing various tasks, including predicting future movements, imputing missing observations, inferring the status of unseen agents, and classifying different global states. Traditional data-driven approaches often handle these tasks separately with special...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	501,616
2202.04176	Crime Hot-Spot Modeling via Topic Modeling and Relative Density Estimation	We present a method to capture groupings of similar calls and determine their relative spatial distribution from a collection of crime record narratives. We first obtain a topic distribution for each narrative, and then propose a nearest neighbors relative density estimation (kNN-RDE) approach to obtain spatial relativ...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	279,477
2304.14767	Dissecting Recall of Factual Associations in Auto-Regressive Language Models	Transformer-based language models (LMs) are known to capture factual knowledge in their parameters. While previous work looked into where factual associations are stored, only little is known about how they are retrieved internally during inference. We investigate this question through the lens of information flow. Giv...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	361,085
2102.11479	Minimally-Supervised Structure-Rich Text Categorization via Learning on Text-Rich Networks	Text categorization is an essential task in Web content analysis. Considering the ever-evolving Web data and new emerging categories, instead of the laborious supervised setting, in this paper, we focus on the minimally-supervised setting that aims to categorize documents effectively, with a couple of seed documents an...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	221,432
2403.04001	Bidirectional Progressive Neural Networks with Episodic Return Progress for Emergent Task Sequencing and Robotic Skill Transfer	Human brain and behavior provide a rich venue that can inspire novel control and learning methods for robotics. In an attempt to exemplify such a development by inspiring how humans acquire knowledge and transfer skills among tasks, we introduce a novel multi-task reinforcement learning framework named Episodic Return ...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	435,413
1101.4343	Fundamental Tradeoffs on Green Wireless Networks	Traditional design of mobile wireless networks mainly focuses on ubiquitous access and large capacity. However, as energy saving and environmental protection become a global demand and inevitable trend, wireless researchers and engineers need to shift their focus to energy-efficiency oriented design, that is, green rad...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,888
2106.03135	Go with the Flows: Mixtures of Normalizing Flows for Point Cloud Generation and Reconstruction	Recently normalizing flows (NFs) have demonstrated state-of-the-art performance on modeling 3D point clouds while allowing sampling with arbitrary resolution at inference time. However, these flow-based models still require long training times and large models for representing complicated geometries. This work enhances...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	239,190
2303.11477	NASDM: Nuclei-Aware Semantic Histopathology Image Generation Using Diffusion Models	In recent years, computational pathology has seen tremendous progress driven by deep learning methods in segmentation and classification tasks aiding prognostic and diagnostic settings. Nuclei segmentation, for instance, is an important task for diagnosing different cancers. However, training deep learning models for n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,868
2207.07303	Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification	Deep learning-based melanoma classification with dermoscopic images has recently shown great potential in automatic early-stage melanoma diagnosis. However, limited by the significant data imbalance and obvious extraneous artifacts, i.e., the hair and ruler markings, discriminative feature extraction from dermoscopic i...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	308,166
1711.00326	The quoter model: a paradigmatic model of the social flow of written information	We propose a model for the social flow of information in the form of text data, which simulates the posting and sharing of short social media posts. Nodes in a graph representing a social network take turns generating words, leading to a symbolic time series associated with each node. Information propagates over the gr...	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	83,697
1302.3209	"Groupware for Groups": Problem-Driven Design in Deme	Design choices can be clarified when group interaction software is directed at solving the interaction needs of particular groups that pre-date the groupware. We describe an example: the Deme platform for online deliberation. Traditional threaded conversation systems are insufficient for solving the problem at which De...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	21,996
2404.19391	ZSMILES: an approach for efficient SMILES storage for random access in Virtual Screening	Virtual screening is a technique used in drug discovery to select the most promising molecules to test in a lab. To perform virtual screening, we need a large set of molecules as input, and storing these molecules can become an issue. In fact, extreme-scale high-throughput virtual screening applications require a big d...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	450,626
1604.04166	Analysis of Interference Correlation in Non-Poisson Networks	The correlation of interference has been well quantified in Poisson networks where the interferers are independent of each other. However, there exists dependence among the base stations (BSs) in wireless networks. In view of this, we quantify the interference correlation in non-Poisson networks where the interferers a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	54,607
2412.02780	WxC-Bench: A Novel Dataset for Weather and Climate Downstream Tasks	High-quality machine learning (ML)-ready datasets play a foundational role in developing new artificial intelligence (AI) models or fine-tuning existing models for scientific applications such as weather and climate analysis. Unfortunately, despite the growing development of new deep learning models for weather and cli...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	513,672
2411.11511	Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning	Model-based reinforcement learning refers to a set of approaches capable of sample-efficient decision making, which create an explicit model of the environment. This model can subsequently be used for learning optimal policies. In this paper, we propose a temporal Gaussian Mixture Model composed of a perception model a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	509,082
2003.06171	Towards a Framework for Visual Intelligence in Service Robotics: Epistemic Requirements and Gap Analysis	A key capability required by service robots operating in real-world, dynamic environments is that of Visual Intelligence, i.e., the ability to use their vision system, reasoning components and background knowledge to make sense of their environment. In this paper, we analyze the epistemic requirements for Visual Intell...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	168,050
2502.12923	On-Device LLMs for Home Assistant: Dual Role in Intent Detection and Response Generation	This paper investigates whether Large Language Models (LLMs), fine-tuned on synthetic but domain-representative data, can perform the twofold task of (i) slot and intent detection and (ii) natural language response generation for a smart home assistant, while running solely on resource-limited, CPU-only edge hardware. ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	535,111
2310.11309	Intelligent Surfaces Aided High-Mobility Communications: Opportunities and Design Issues	Intelligent reflecting/refracting surface (IRS) is envisioned as a promising technology to reconfigure wireless propagation environment for enhancing the communication performance, by smartly controlling the signal reflection/refraction with a large number of tunable passive elements. In particular, the application of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	400,593
1701.08888	Integrating Reviews into Personalized Ranking for Cold Start Recommendation	Item recommendation task predicts a personalized ranking over a set of items for each individual user. One paradigm is the rating-based methods that concentrate on explicit feedbacks and hence face the difficulties in collecting them. Meanwhile, the ranking-based methods are presented with rated items and then rank the...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	67,546
cmp-lg/9612003	Metrics for Evaluating Dialogue Strategies in a Spoken Language System	In this paper, we describe a set of metrics for the evaluation of different dialogue management strategies in an implemented real-time spoken language system. The set of metrics we propose offers useful insights in evaluating how particular choices in the dialogue management can affect the overall quality of the man-ma...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,681
2501.14808	HyGen: Efficient LLM Serving via Elastic Online-Offline Request Co-location	Large language models (LLMs) have facilitated a wide range of applications with distinct service-level objectives (SLOs), from latency-sensitive online tasks like interactive chatbots to throughput-oriented offline workloads like document summarization. The existing deployment model, which dedicates machines to each wo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	527,282
1310.2632	Bilinear Generalized Approximate Message Passing	We extend the generalized approximate message passing (G-AMP) approach, originally proposed for high-dimensional generalized-linear regression in the context of compressive sensing, to the generalized-bilinear case, which enables its application to matrix completion, robust PCA, dictionary learning, and related matrix-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	27,690
2405.15544	Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property Prediction	Recently, few-shot molecular property prediction (FSMPP) has garnered increasing attention. Despite impressive breakthroughs achieved by existing methods, they often overlook the inherent many-to-many relationships between molecules and properties, which limits their performance. For instance, similar substructures of ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	456,985
2407.00629	Identification of LFT Structured Descriptor Systems with Slow and Non-uniform Sampling	Time domain identification is studied in this paper for parameters of a continuous-time multi-input multi-output descriptor system, with these parameters affecting system matrices through a linear fractional transformation. Sampling is permitted to be slow and non-uniform, and there are no necessities to satisfy the Ny...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	468,942
2410.02074	Price-guided user attention in large-scale E-commerce group recommendation	Existing group recommender systems utilize attention mechanisms to identify critical users who influence group decisions the most. We analyzed user attention scores from a widely-used group recommendation model on a real-world E-commerce dataset and found that item price and user interaction history significantly influ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	494,087
2401.13530	Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space	Recently, optimization on the Riemannian manifold has provided new insights to the optimization community. In this regard, the manifold taken as the probability measure metric space equipped with the second-order Wasserstein distance is of particular interest, since optimization on it can be linked to practical samplin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	423,756
1805.00116	A Canonical Image Set for Examining and Comparing Image Processing Algorithms	The purpose of this paper is to introduce a set of four test images containing features and structures that can facilitate effective examination and comparison of image processing algorithms. More specifically, the images are designed to more explicitly expose the characteristic properties of algorithms for image compr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	96,359
1701.08289	Face Detection using Deep Learning: An Improved Faster RCNN Approach	In this report, we present a new face detection scheme using deep learning and achieve the state-of-the-art detection performance on the well-known FDDB face detetion benchmark evaluation. In particular, we improve the state-of-the-art faster RCNN framework by combining a number of strategies, including feature concate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	67,438
2306.02029	Model-aided Federated Reinforcement Learning for Multi-UAV Trajectory Planning in IoT Networks	Deploying teams of unmanned aerial vehicles (UAVs) to harvest data from distributed Internet of Things (IoT) devices requires efficient trajectory planning and coordination algorithms. Multi-agent reinforcement learning (MARL) has emerged as a solution, but requires extensive and costly real-world training data. To tac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	370,729
2501.18062	FinanceQA: A Benchmark for Evaluating Financial Analysis Capabilities of Large Language Models	FinanceQA is a testing suite that evaluates LLMs' performance on complex numerical financial analysis tasks that mirror real-world investment work. Despite recent advances, current LLMs fail to meet the strict accuracy requirements of financial institutions, with models failing approximately 60% of realistic tasks that...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	528,551
1807.01442	Modeling Sparse Deviations for Compressed Sensing using Generative Models	In compressed sensing, a small number of linear measurements can be used to reconstruct an unknown signal. Existing approaches leverage assumptions on the structure of these signals, such as sparsity or the availability of a generative model. A domain-specific generative model can provide a stronger prior and thus allo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	102,063
2202.01463	Minimax rate of consistency for linear models with missing values	Missing values arise in most real-world data sets due to the aggregation of multiple sources and intrinsically missing information (sensor failure, unanswered questions in surveys...). In fact, the very nature of missing values usually prevents us from running standard learning algorithms. In this paper, we focus on th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,491
2204.05104	Self-Supervised Graph Neural Network for Multi-Source Domain Adaptation	Domain adaptation (DA) tries to tackle the scenarios when the test data does not fully follow the same distribution of the training data, and multi-source domain adaptation (MSDA) is very attractive for real world applications. By learning from large-scale unlabeled samples, self-supervised learning has now become a ne...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	290,911
2310.08095	Multi-Satellite Cooperative Networks: Joint Hybrid Beamforming and User Scheduling Design	In this paper, we consider a cooperative communication network where multiple low-Earth-orbit (LEO) satellites provide services to multiple ground users (GUs) cooperatively at the same time and on the same frequency. The multi-satellite cooperation has great potential in extending communication coverage and increasing ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	399,263
2302.10879	$k$NN-Adapter: Efficient Domain Adaptation for Black-Box Language Models	Fine-tuning a language model on a new domain is standard practice for domain adaptation. However, it can be infeasible when it comes to modern large-scale language models such as GPT-3, which can only be accessed through APIs, making it difficult to access the internal parameters of the model. In this paper, we propose...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	346,990
2001.00329	On Consequentialism and Fairness	Recent work on fairness in machine learning has primarily emphasized how to define, quantify, and encourage "fair" outcomes. Less attention has been paid, however, to the ethical foundations which underlie such efforts. Among the ethical perspectives that should be taken into consideration is consequentialism, the posi...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	159,186
2109.06073	An End-to-end Point of Interest (POI) Conflation Framework	Point of interest (POI) data serves as a valuable source of semantic information for places of interest and has many geospatial applications in real estate, transportation, and urban planning. With the availability of different data sources, POI conflation serves as a valuable technique for enriching data quality and c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	255,035
2205.01858	DeeptDCS: Deep Learning-Based Estimation of Currents Induced During Transcranial Direct Current Stimulation	Objective: Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique used to generate conduction currents in the head and disrupt brain functions. To rapidly evaluate the tDCS-induced current density in near real-time, this paper proposes a deep learning-based emulator, named DeeptDCS...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	294,740
2109.10982	Quantifying nonlocality: how outperforming local quantum codes is expensive	Quantum low-density parity-check (LDPC) codes are a promising avenue to reduce the cost of constructing scalable quantum circuits. However, it is unclear how to implement these codes in practice. Seminal results of Bravyi & Terhal, and Bravyi, Poulin & Terhal have shown that quantum LDPC codes implemented through local...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	256,805
2011.14894	Uncertainty-driven ensembles of deep architectures for multiclass classification. Application to COVID-19 diagnosis in chest X-ray images	Respiratory diseases kill million of people each year. Diagnosis of these pathologies is a manual, time-consuming process that has inter and intra-observer variability, delaying diagnosis and treatment. The recent COVID-19 pandemic has demonstrated the need of developing systems to automatize the diagnosis of pneumonia...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	208,920
2112.06667	Long-Term Benefits of Network Boosters for Renewables Integration and Corrective Grid Security	The preventative strategies for $N-1$ network security dominant in European networks mean that network capacity is kept free in case a line fails. If instead fast corrective actions are used to overcome network overloading when single lines fail, this has the potential to free up network capacity that is otherwise unde...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	271,258
0711.3605	Very strict selectional restrictions	We discuss the characteristics and behaviour of two parallel classes of verbs in two Romance languages, French and Portuguese. Examples of these verbs are Port. abater [gado] and Fr. abattre [b\'etail], both meaning "slaughter [cattle]". In both languages, the definition of the class of verbs includes several features:...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	944
2401.04988	Optimising Graph Representation for Hardware Implementation of Graph Convolutional Networks for Event-based Vision	Event-based vision is an emerging research field involving processing data generated by Dynamic Vision Sensors (neuromorphic cameras). One of the latest proposals in this area are Graph Convolutional Networks (GCNs), which allow to process events in its original sparse form while maintaining high detection and classifi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	420,615
2105.04017	Infill topology and shape optimisation of lattice-skin structures	Lattice-skin structures composed of a thin-shell skin and a lattice infill are widespread in nature and large-scale engineering due to their efficiency and exceptional mechanical properties. Recent advances in additive manufacturing, or 3D printing, make it possible to create lattice-skin structures of almost any size ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	234,347
1912.11747	Score and Lyrics-Free Singing Voice Generation	Generative models for singing voice have been mostly concerned with the task of ``singing voice synthesis,'' i.e., to produce singing voice waveforms given musical scores and text lyrics. In this work, we explore a novel yet challenging alternative: singing voice generation without pre-assigned scores and lyrics, in bo...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	158,651
1907.04235	A Simple Derivation of AMP and its State Evolution via First-Order Cancellation	We consider the linear regression problem, where the goal is to recover the vector $\boldsymbol{x}\in\mathbb{R}^n$ from measurements $\boldsymbol{y}=\boldsymbol{A}\boldsymbol{x}+\boldsymbol{w}\in\mathbb{R}^m$ under known matrix $\boldsymbol{A}$ and unknown noise $\boldsymbol{w}$. For large i.i.d. sub-Gaussian $\boldsym...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	138,056
1908.05596	Two-stage Federated Phenotyping and Patient Representation Learning	A large percentage of medical information is in unstructured text format in electronic medical record systems. Manual extraction of information from clinical notes is extremely time consuming. Natural language processing has been widely used in recent years for automatic information extraction from medical texts. Howev...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	141,753
2004.10382	Image Processing Failure and Deep Learning Success in Lawn Measurement	Lawn area measurement is an application of image processing and deep learning. Researchers have been used hierarchical networks, segmented images and many other methods to measure lawn area. Methods effectiveness and accuracy varies. In this project Image processing and deep learning methods has been compared to find t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	173,620
2410.20735	Murine AI excels at cats and cheese: Structural differences between human and mouse neurons and their implementation in generative AIs	Mouse and human brains have different functions that depend on their neuronal networks. In this study, we analyzed nanometer-scale three-dimensional structures of brain tissues of the mouse medial prefrontal cortex and compared them with structures of the human anterior cingulate cortex. The obtained results indicated ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	502,939
2303.05329	Tucker Bilinear Attention Network for Multi-scale Remote Sensing Object Detection	Object detection on VHR remote sensing images plays a vital role in applications such as urban planning, land resource management, and rescue missions. The large-scale variation of the remote-sensing targets is one of the main challenges in VHR remote-sensing object detection. Existing methods improve the detection acc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	350,425
1803.00118	Surges of collective human activity emerge from simple pairwise correlations	Human populations exhibit complex behaviors---characterized by long-range correlations and surges in activity---across a range of social, political, and technological contexts. Yet it remains unclear where these collective behaviors come from, or if there even exists a set of unifying principles. Indeed, existing expla...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	91,594
2212.06882	Envisioning a Human-AI collaborative system to transform policies into decision models	Regulations govern many aspects of citizens' daily lives. Governments and businesses routinely automate these in the form of coded rules (e.g., to check a citizen's eligibility for specific benefits). However, the path to automation is long and challenging. To address this, recent global initiatives for digital governm...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	336,239
2304.13479	Fundamental Tradeoffs in Learning with Prior Information	We seek to understand fundamental tradeoffs between the accuracy of prior information that a learner has on a given problem and its learning performance. We introduce the notion of prioritized risk, which differs from traditional notions of minimax and Bayes risk by allowing us to study such fundamental tradeoffs in se...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	360,591
2210.00025	Artificial Replay: A Meta-Algorithm for Harnessing Historical Data in Bandits	Most real-world deployments of bandit algorithms exist somewhere in between the offline and online set-up, where some historical data is available upfront and additional data is collected dynamically online. How best to incorporate historical data to "warm start" bandit algorithms is an open question: naively initializ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	320,692
2312.09778	Hypergraph-MLP: Learning on Hypergraphs without Message Passing	Hypergraphs are vital in modelling data with higher-order relations containing more than two entities, gaining prominence in machine learning and signal processing. Many hypergraph neural networks leverage message passing over hypergraph structures to enhance node representation learning, yielding impressive performanc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	415,874
1807.05324	Generating Synthetic Data for Neural Keyword-to-Question Models	Search typically relies on keyword queries, but these are often semantically ambiguous. We propose to overcome this by offering users natural language questions, based on their keyword queries, to disambiguate their intent. This keyword-to-question task may be addressed using neural machine translation techniques. Neur...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	102,903
1105.0256	Easy-to-compute parameterizations of all wavelet filters: input-output and state-space	We here use notions from the theory linear shift-invariant dynamical systems to provide an easy-to-compute characterization of all rational wavelet filters. For a given N bigger or equql to 2, the number of inputs, the construction is based on a factorization to an elementary wavelet filter along with of m elementary u...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	10,204
1908.06003	Exploring Properties of Icosoku by Constraint Satisfaction Approach	Icosoku is a challenging and interesting puzzle that exhibits highly symmetrical and combinatorial nature. In this paper, we pose the questions derived from the puzzle, but with more difficulty and generality. In addition, we also present a constraint programming model for the proposed questions, which can provide the ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	141,879
2404.04887	A Clinical-oriented Multi-level Contrastive Learning Method for Disease Diagnosis in Low-quality Medical Images	Representation learning offers a conduit to elucidate distinctive features within the latent space and interpret the deep models. However, the randomness of lesion distribution and the complexity of low-quality factors in medical images pose great challenges for models to extract key lesion features. Disease diagnosis ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,842
1907.03336	Search-Based Serving Architecture of Embeddings-Based Recommendations	Over the past 10 years, many recommendation techniques have been based on embedding users and items in latent vector spaces, where the inner product of a (user,item) pair of vectors represents the predicted affinity of the user to the item. A wealth of literature has focused on the various modeling approaches that resu...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	137,837
2104.12827	Learning-based decentralized offloading decision making in an adversarial environment	Vehicular fog computing (VFC) pushes the cloud computing capability to the distributed fog nodes at the edge of the Internet, enabling compute-intensive and latency-sensitive computing services for vehicles through task offloading. However, a heterogeneous mobility environment introduces uncertainties in terms of resou...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	232,321
2408.07718	Impact of Inaccurate Contamination Ratio on Robust Unsupervised Anomaly Detection	Training data sets intended for unsupervised anomaly detection, typically presumed to be anomaly-free, often contain anomalies (or contamination), a challenge that significantly undermines model performance. Most robust unsupervised anomaly detection models rely on contamination ratio information to tackle contaminatio...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	480,699
2406.15581	Necessary and sufficient condition for neutral-type delay systems: Polynomial approximations	A new necessary and sufficient stability test in a tractable number of operations for linear neutral-type delay systems is introduced. It is developed in the Lyapunov-Krasovskii framework via functionals with prescribed derivatives. The necessary conditions, which stem from substituting any polynomial approximation of ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	466,783
2303.01684	BO-Muse: A human expert and AI teaming framework for accelerated experimental design	In this paper we introduce BO-Muse, a new approach to human-AI teaming for the optimization of expensive black-box functions. Inspired by the intrinsic difficulty of extracting expert knowledge and distilling it back into AI models and by observations of human behavior in real-world experimental design, our algorithm l...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	349,060
1710.02081	Online Photometric Calibration for Auto Exposure Video for Realtime Visual Odometry and SLAM	Recent direct visual odometry and SLAM algorithms have demonstrated impressive levels of precision. However, they require a photometric camera calibration in order to achieve competitive results. Hence, the respective algorithm cannot be directly applied to an off-the-shelf-camera or to a video sequence acquired with a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	82,104
2204.03776	TorMentor: Deterministic dynamic-path, data augmentations with fractals	We propose the use of fractals as a means of efficient data augmentation. Specifically, we employ plasma fractals for adapting global image augmentation transformations into continuous local transforms. We formulate the diamond square algorithm as a cascade of simple convolution operations allowing efficient computatio...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	290,431
2306.01638	Do we become wiser with time? On causal equivalence with tiered background knowledge	Equivalence classes of DAGs (represented by CPDAGs) may be too large to provide useful causal information. Here, we address incorporating tiered background knowledge yielding restricted equivalence classes represented by 'tiered MPDAGs'. Tiered knowledge leads to considerable gains in informativeness and computational ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	370,522
2003.04151	Embedding Propagation: Smoother Manifold for Few-Shot Classification	Few-shot classification is challenging because the data distribution of the training set can be widely different to the test set as their classes are disjoint. This distribution shift often results in poor generalization. Manifold smoothing has been shown to address the distribution shift problem by extending the decis...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	167,466
2412.17003	Anonymous Shamir's Secret Sharing via Reed-Solomon Codes Against Permutations, Insertions, and Deletions	In this work, we study the performance of Reed-Solomon codes against an adversary that first permutes the symbols of the codeword and then performs insertions and deletions. This adversarial model is motivated by the recent interest in fully anonymous secret-sharing schemes [EBG+24],[BGI+24]. A fully anonymous secret-s...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	519,790
2309.00514	A Machine Vision Method for Correction of Eccentric Error: Based on Adaptive Enhancement Algorithm	In the procedure of surface defects detection for large-aperture aspherical optical elements, it is of vital significance to adjust the optical axis of the element to be coaxial with the mechanical spin axis accurately. Therefore, a machine vision method for eccentric error correction is proposed in this paper. Focusin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	389,326
2404.08869	Misinformation Resilient Search Rankings with Webgraph-based Interventions	The proliferation of unreliable news domains on the internet has had wide-reaching negative impacts on society. We introduce and evaluate interventions aimed at reducing traffic to unreliable news domains from search engines while maintaining traffic to reliable domains. We build these interventions on the principles o...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	446,439
2201.06924	A Synthetic Prediction Market for Estimating Confidence in Published Work	Explainably estimating confidence in published scholarly work offers opportunity for faster and more robust scientific progress. We develop a synthetic prediction market to assess the credibility of published claims in the social and behavioral sciences literature. We demonstrate our system and detail our findings usin...	false	false	false	false	true	true	true	false	false	false	false	false	false	true	true	false	false	false	275,877
2201.07705	GEMEL: Model Merging for Memory-Efficient, Real-Time Video Analytics at the Edge	Video analytics pipelines have steadily shifted to edge deployments to reduce bandwidth overheads and privacy violations, but in doing so, face an ever-growing resource tension. Most notably, edge-box GPUs lack the memory needed to concurrently house the growing number of (increasingly complex) models for real-time inf...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	276,109
1901.01855	A* Tree Search for Portfolio Management	We propose a planning-based method to teach an agent to manage portfolio from scratch. Our approach combines deep reinforcement learning techniques with search techniques like AlphaGo. By uniting the advantages in A* search algorithm with Monte Carlo tree search, we come up with a new algorithm named A* tree search in ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	118,065
1704.05123	Resolution-Exact Planner for Thick Non-Crossing 2-Link Robots	We consider the path planning problem for a 2-link robot amidst polygonal obstacles. Our robot is parametrizable by the lengths $\ell_1, \ell_2>0$ of its two links, the thickness $\tau \ge 0$ of the links, and an angle $\kappa$ that constrains the angle between the 2 links to be strictly greater than $\kappa$. The case...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	71,942
2302.14386	Practical Algorithms for Orientations of Partially Directed Graphical Models	In observational studies, the true causal model is typically unknown and needs to be estimated from available observational and limited experimental data. In such cases, the learned causal model is commonly represented as a partially directed acyclic graph (PDAG), which contains both directed and undirected edges indic...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	348,274
2209.09185	Active Inference for Autonomous Decision-Making with Contextual Multi-Armed Bandits	In autonomous robotic decision-making under uncertainty, the tradeoff between exploitation and exploration of available options must be considered. If secondary information associated with options can be utilized, such decision-making problems can often be formulated as contextual multi-armed bandits (CMABs). In this s...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	318,415
2408.16849	Machine Learning-Based Research on the Adaptability of Adolescents to Online Education	With the rapid advancement of internet technology, the adaptability of adolescents to online learning has emerged as a focal point of interest within the educational sphere. However, the academic community's efforts to develop predictive models for adolescent online learning adaptability require further refinement and ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	484,469
1609.04602	New MDS or near MDS self-dual codes over finite fields	The study of MDS self-dual codes has attracted lots of attention in recent years. There are many papers on determining existence of $q-$ary MDS self-dual codes for various lengths. There are not existence of $q-$ary MDS self-dual codes of some lengths, even these lengths $< q$. We generalize MDS Euclidean self-du...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	61,009
1606.03838	Laplacian LRR on Product Grassmann Manifolds for Human Activity Clustering in Multi-Camera Video Surveillance	In multi-camera video surveillance, it is challenging to represent videos from different cameras properly and fuse them efficiently for specific applications such as human activity recognition and clustering. In this paper, a novel representation for multi-camera video data, namely the Product Grassmann Manifold (PGM),...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	57,153
2310.14028	GASCOM: Graph-based Attentive Semantic Context Modeling for Online Conversation Understanding	Online conversation understanding is an important yet challenging NLP problem which has many useful applications (e.g., hate speech detection). However, online conversations typically unfold over a series of posts and replies to those posts, forming a tree structure within which individual posts may refer to semantic c...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	401,679
1310.3358	A Kalman Filtering approach of improved precision for fault diagnosis in distributed parameter systems	The Derivative-free nonlinear Kalman Filter is proposed for state estimation and fault diagnosis in distributed parameter systems and particularly in dynamical systems described by partial differential equations of the nonlinear wave type. At a first stage, a nonlinear filtering approach for estimating the dynamics of ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	27,738
2412.10424	LLM-as-an-Interviewer: Beyond Static Testing Through Dynamic LLM Evaluation	We introduce LLM-as-an-Interviewer, a novel paradigm for evaluating large language models (LLMs). This approach leverages multi-turn interactions where the LLM interviewer actively provides feedback on responses and poses follow-up questions to the evaluated LLM. At the start of the interview, the LLM interviewer dynam...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	516,915
2011.03742	Fast 3D Modeling of Anthropomorphic Robotic Hands Based on A Multi-layer Deformable Design	Current anthropomorphic robotic hands mainly focus on improving their dexterity by devising new mechanical structures and actuation systems. However, most of them rely on a single structure/system (e.g., bone-only) and ignore the fact that the human hand is composed of multiple functional structures (e.g., skin, bones,...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	205,338
2312.08022	Mono3DVG: 3D Visual Grounding in Monocular Images	We introduce a novel task of 3D visual grounding in monocular RGB images using language descriptions with both appearance and geometry information. Specifically, we build a large-scale dataset, Mono3DRefer, which contains 3D object targets with their corresponding geometric text descriptions, generated by ChatGPT and r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	415,162
1807.07998	Convolutional Neural Networks Analyzed via Inverse Problem Theory and Sparse Representations	Inverse problems in imaging such as denoising, deblurring, superresolution (SR) have been addressed for many decades. In recent years, convolutional neural networks (CNNs) have been widely used for many inverse problem areas. Although their indisputable success, CNNs are not mathematically validated as to how and what ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	103,431
1701.04851	Synthesizing Normalized Faces from Facial Identity Features	We present a method for synthesizing a frontal, neutral-expression image of a person's face given an input face photograph. This is achieved by learning to generate facial landmarks and textures from features extracted from a facial-recognition network. Unlike previous approaches, our encoding feature vector is largely...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	66,896
2406.11070	Fine-grained Classes and How to Find Them	In many practical applications, coarse-grained labels are readily available compared to fine-grained labels that reflect subtle differences between classes. However, existing methods cannot leverage coarse labels to infer fine-grained labels in an unsupervised manner. To bridge this gap, we propose FALCON, a method tha...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	464,702
2305.19582	Causal Discovery with Latent Confounders Based on Higher-Order Cumulants	Causal discovery with latent confounders is an important but challenging task in many scientific areas. Despite the success of some overcomplete independent component analysis (OICA) based methods in certain domains, they are computationally expensive and can easily get stuck into local optima. We notice that interesti...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	369,591
2401.09032	Improved Consensus ADMM for Cooperative Motion Planning of Large-Scale Connected Autonomous Vehicles with Limited Communication	This paper investigates a cooperative motion planning problem for large-scale connected autonomous vehicles (CAVs) under limited communications, which addresses the challenges of high communication and computing resource requirements. Our proposed methodology incorporates a parallel optimization algorithm with improved...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	422,122
2212.07907	Automatic vehicle trajectory data reconstruction at scale	In this paper we propose an automatic trajectory data reconciliation to correct common errors in vision-based vehicle trajectory data. Given "raw" vehicle detection and tracking information from automatic video processing algorithms, we propose a pipeline including (a) an online data association algorithm to match frag...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	336,564
2411.05750	On Differentially Private String Distances	Given a database of bit strings $A_1,\ldots,A_m\in \{0,1\}^n$, a fundamental data structure task is to estimate the distances between a given query $B\in \{0,1\}^n$ with all the strings in the database. In addition, one might further want to ensure the integrity of the database by releasing these distance statistics in...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	true	506,775
2306.15333	Shoggoth: Towards Efficient Edge-Cloud Collaborative Real-Time Video Inference via Adaptive Online Learning	This paper proposes Shoggoth, an efficient edge-cloud collaborative architecture, for boosting inference performance on real-time video of changing scenes. Shoggoth uses online knowledge distillation to improve the accuracy of models suffering from data drift and offloads the labeling process to the cloud, alleviating ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	375,987
2209.07946	Transport in reservoir computing	Reservoir computing systems are constructed using a driven dynamical system in which external inputs can alter the evolving states of a system. These paradigms are used in information processing, machine learning, and computation. A fundamental question that needs to be addressed in this framework is the statistical re...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	317,952
2207.11447	Handling Data Heterogeneity in Federated Learning via Knowledge Distillation and Fusion	Federated learning (FL) supports distributed training of a global machine learning model across multiple devices with the help of a central server. However, data heterogeneity across different devices leads to the client model drift issue and results in model performance degradation and poor model fairness. To address ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	309,642

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