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
1302.4973	Strong Completeness and Faithfulness in Bayesian Networks	A completeness result for d-separation applied to discrete Bayesian networks is presented and it is shown that in a strong measure-theoretic sense almost all discrete distributions for a given network structure are faithful; i.e. the independence facts true of the distribution are all and only those entailed by the net...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,247
2412.03514	Adaptive Personalized Over-the-Air Federated Learning with Reflecting Intelligent Surfaces	Over-the-air federated learning (OTA-FL) unifies communication and model aggregation by leveraging the inherent superposition property of the wireless medium. This strategy can enable scalable and bandwidth-efficient learning via simultaneous transmission of model updates using the same frequency resources, if care is ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	513,986
1409.2620	Learning Machines Implemented on Non-Deterministic Hardware	This paper highlights new opportunities for designing large-scale machine learning systems as a consequence of blurring traditional boundaries that have allowed algorithm designers and application-level practitioners to stay -- for the most part -- oblivious to the details of the underlying hardware-level implementatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	35,925
2405.02954	Source-Free Domain Adaptation Guided by Vision and Vision-Language Pre-Training	Source-free domain adaptation (SFDA) aims to adapt a source model trained on a fully-labeled source domain to a related but unlabeled target domain. While the source model is a key avenue for acquiring target pseudolabels, the generated pseudolabels may exhibit source bias. In the conventional SFDA pipeline, a large da...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	451,991
2301.00646	Addressing the Selection Bias in Voice Assistance: Training Voice Assistance Model in Python with Equal Data Selection	In recent times, voice assistants have become a part of our day-to-day lives, allowing information retrieval by voice synthesis, voice recognition, and natural language processing. These voice assistants can be found in many modern-day devices such as Apple, Amazon, Google, and Samsung. This project is primarily focuse...	false	false	true	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	338,975
1105.2096	Sum Capacity of Gaussian Interfering Multiple Access Channels in the Low Interference Regime	This paper has been withdrawn due to an incorrect proof.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	10,322
1011.2686	A Discrete Time Markov Chain Model for High Throughput Bidirectional Fano Decoders	The bidirectional Fano algorithm (BFA) can achieve at least two times decoding throughput compared to the conventional unidirectional Fano algorithm (UFA). In this paper, bidirectional Fano decoding is examined from the queuing theory perspective. A Discrete Time Markov Chain (DTMC) is employed to model the BFA decoder...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,203
1707.02244	GPU-Accelerated Algorithms for Compressed Signals Recovery with Application to Astronomical Imagery Deblurring	Compressive sensing promises to enable bandwidth-efficient on-board compression of astronomical data by lifting the encoding complexity from the source to the receiver. The signal is recovered off-line, exploiting GPUs parallel computation capabilities to speedup the reconstruction process. However, inherent GPU hardwa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	76,668
2307.08655	Multilingual Speech-to-Speech Translation into Multiple Target Languages	Speech-to-speech translation (S2ST) enables spoken communication between people talking in different languages. Despite a few studies on multilingual S2ST, their focus is the multilinguality on the source side, i.e., the translation from multiple source languages to one target language. We present the first work on mul...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	379,887
2201.07421	Online Distributed Coordinated Precoding for Virtualized MIMO Networks with Delayed CSI	We consider online wireless network virtualization (WNV) in a multi-cell multiple-input multiple output (MIMO) system with delayed feedback of channel state information (CSI). Multiple service providers (SPs) simultaneously share the base station resources of an infrastructure provider (InP). We aim at minimizing the a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	276,022
1906.00547	MaxGap Bandit: Adaptive Algorithms for Approximate Ranking	This paper studies the problem of adaptively sampling from K distributions (arms) in order to identify the largest gap between any two adjacent means. We call this the MaxGap-bandit problem. This problem arises naturally in approximate ranking, noisy sorting, outlier detection, and top-arm identification in bandits. Th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	133,425
2412.04930	Video Decomposition Prior: A Methodology to Decompose Videos into Layers	In the evolving landscape of video enhancement and editing methodologies, a majority of deep learning techniques often rely on extensive datasets of observed input and ground truth sequence pairs for optimal performance. Such reliance often falters when acquiring data becomes challenging, especially in tasks like video...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	514,633
1905.03696	HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precision	Model size and inference speed/power have become a major challenge in the deployment of Neural Networks for many applications. A promising approach to address these problems is quantization. However, uniformly quantizing a model to ultra low precision leads to significant accuracy degradation. A novel solution for this...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	130,263
2411.05361	Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks	Multimodal foundation models, such as Gemini and ChatGPT, have revolutionized human-machine interactions by seamlessly integrating various forms of data. Developing a universal spoken language model that comprehends a wide range of natural language instructions is critical for bridging communication gaps and facilitati...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	506,646
2208.14820	Learning Automata-Based Complex Event Patterns in Answer Set Programming	Complex Event Recognition and Forecasting (CER/F) techniques attempt to detect, or even forecast ahead of time, event occurrences in streaming input using predefined event patterns. Such patterns are not always known in advance, or they frequently change over time, making machine learning techniques, capable of extract...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	315,427
2307.14152	Investigating the Impact of Variables on Handover Performance in 5G Ultra-Dense Networks	The advent of 5G New Radio (NR) technology has revolutionized the landscape of wireless communication, offering various enhancements such as elevated system capacity, improved spectrum efficiency, and higher data transmission rates. To achieve these benefits, 5G has implemented the Ultra-Dense Network (UDN) architectur...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	381,832
1604.03246	Radio Resource Allocation for Device-to-Device Underlay Communication Using Hypergraph Theory	Device-to-Device (D2D) communication has been recognized as a promising technique to offload the traffic for the evolved Node B (eNB). However, the D2D transmission as an underlay causes severe interference to both the cellular and other D2D links, which imposes a great technical challenge to radio resource allocation....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	54,470
2309.07983	SLMIA-SR: Speaker-Level Membership Inference Attacks against Speaker Recognition Systems	Membership inference attacks allow adversaries to determine whether a particular example was contained in the model's training dataset. While previous works have confirmed the feasibility of such attacks in various applications, none has focused on speaker recognition (SR), a promising voice-based biometric recognition...	false	false	true	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	391,985
2211.05322	On Optimizing the Communication of Model Parallelism	We study a novel and important communication pattern in large-scale model-parallel deep learning (DL), which we call cross-mesh resharding. This pattern emerges when the two paradigms of model parallelism - intra-operator and inter-operator parallelism - are combined to support large models on large clusters. In cross-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	329,514
2411.01211	Spatial Transformers for Radio Map Estimation	Radio map estimation (RME) involves spatial interpolation of radio measurements to predict metrics such as the received signal strength at locations where no measurements were collected. The most popular estimators nowadays project the measurement locations to a regular grid and complete the resulting measurement tenso...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	504,962
2210.07881	Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate	Decentralized optimization is an emerging paradigm in distributed learning in which agents achieve network-wide solutions by peer-to-peer communication without the central server. Since communication tends to be slower than computation, when each agent communicates with only a few neighboring agents per iteration, they...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	323,904
2404.00566	CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks	To adequately test modern code generation systems, evaluation benchmarks must execute and test the code generated by the system. However, these execution and testing requirements have largely limited benchmarks to settings where code is easily executable or has human-written tests. To facilitate evaluation of code gene...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	442,997
2312.04226	Dynamic Data-Driven Digital Twins for Blockchain Systems	In recent years, we have seen an increase in the adoption of blockchain-based systems in non-financial applications, looking to benefit from what the technology has to offer. Although many fields have managed to include blockchain in their core functionalities, the adoption of blockchain, in general, is constrained by ...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	true	413,602
2204.11830	Proto2Proto: Can you recognize the car, the way I do?	Prototypical methods have recently gained a lot of attention due to their intrinsic interpretable nature, which is obtained through the prototypes. With growing use cases of model reuse and distillation, there is a need to also study transfer of interpretability from one model to another. We present Proto2Proto, a nove...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,275
1811.01742	META-DES.H: a dynamic ensemble selection technique using meta-learning and a dynamic weighting approach	In Dynamic Ensemble Selection (DES) techniques, only the most competent classifiers are selected to classify a given query sample. Hence, the key issue in DES is how to estimate the competence of each classifier in a pool to select the most competent ones. In order to deal with this issue, we proposed a novel dynamic e...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	112,436
2011.13307	Polygon-free: Unconstrained Scene Text Detection with Box Annotations	Although a polygon is a more accurate representation than an upright bounding box for text detection, the annotations of polygons are extremely expensive and challenging. Unlike existing works that employ fully-supervised training with polygon annotations, this study proposes an unconstrained text detection system term...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	208,436
2410.20518	MidiTok Visualizer: a tool for visualization and analysis of tokenized MIDI symbolic music	Symbolic music research plays a crucial role in music-related machine learning, but MIDI data can be complex for those without musical expertise. To address this issue, we present MidiTok Visualizer, a web application designed to facilitate the exploration and visualization of various MIDI tokenization methods from the...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	502,845
2309.06981	MASTERKEY: Practical Backdoor Attack Against Speaker Verification Systems	Speaker Verification (SV) is widely deployed in mobile systems to authenticate legitimate users by using their voice traits. In this work, we propose a backdoor attack MASTERKEY, to compromise the SV models. Different from previous attacks, we focus on a real-world practical setting where the attacker possesses no know...	false	false	true	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	391,612
2406.13856	Kishu: Time-Traveling for Computational Notebooks (Technical Report)	Computational notebooks (e.g., Jupyter, Google Colab) are widely used by data scientists. A key feature of notebooks is the interactive computing model of iteratively executing cells (i.e., a set of statements) and observing the result (e.g., model or plot). Unfortunately, existing notebook systems do not offer time-tr...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	466,023
1812.03928	Learning Representations of Sets through Optimized Permutations	Representations of sets are challenging to learn because operations on sets should be permutation-invariant. To this end, we propose a Permutation-Optimisation module that learns how to permute a set end-to-end. The permuted set can be further processed to learn a permutation-invariant representation of that set, avoid...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	116,107
2105.08621	Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks	With the ever-increasing popularity and applications of graph neural networks, several proposals have been made to explain and understand the decisions of a graph neural network. Explanations for graph neural networks differ in principle from other input settings. It is important to attribute the decision to input feat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	235,814
2103.01342	Reinforcement Learning for Adaptive Mesh Refinement	Large-scale finite element simulations of complex physical systems governed by partial differential equations (PDE) crucially depend on adaptive mesh refinement (AMR) to allocate computational budget to regions where higher resolution is required. Existing scalable AMR methods make heuristic refinement decisions based ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	222,584
2009.13232	ECGDetect: Detecting Ischemia via Deep Learning	Coronary artery disease(CAD) is the most common type of heart disease and the leading cause of death worldwide[1]. A progressive state of this disease marked by plaque rupture and clot formation in the coronary arteries, also known as an acute coronary syndrome (ACS), is a condition of the heart associated with sudden,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	197,675
2211.11025	Self-supervised iRegNet for the Registration of Longitudinal Brain MRI of Diffuse Glioma Patients	Reliable and accurate registration of patient-specific brain magnetic resonance imaging (MRI) scans containing pathologies is challenging due to tissue appearance changes. This paper describes our contribution to the Registration of the longitudinal brain MRI task of the Brain Tumor Sequence Registration Challenge 2022...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	331,544
2108.10515	ARShoe: Real-Time Augmented Reality Shoe Try-on System on Smartphones	Virtual try-on technology enables users to try various fashion items using augmented reality and provides a convenient online shopping experience. However, most previous works focus on the virtual try-on for clothes while neglecting that for shoes, which is also a promising task. To this concern, this work proposes a r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	251,917
2008.09228	AWNet: Attentive Wavelet Network for Image ISP	As the revolutionary improvement being made on the performance of smartphones over the last decade, mobile photography becomes one of the most common practices among the majority of smartphone users. However, due to the limited size of camera sensors on phone, the photographed image is still visually distinct to the on...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	192,644
2404.15958	Platooning of Heterogeneous Vehicles with Actuation Delays: Theoretical and Experimental Results	In this paper we present a prediction-based Cooperative Adaptive Cruise Controller for vehicles with actuation delay, applicable within heterogeneous platoons. We provide a stability analysis for the discrete-time implementation of this controller, which shows the effect of the used sampling times and can be used for s...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	449,297
2011.03346	DeepDFT: Neural Message Passing Network for Accurate Charge Density Prediction	We introduce DeepDFT, a deep learning model for predicting the electronic charge density around atoms, the fundamental variable in electronic structure simulations from which all ground state properties can be calculated. The model is formulated as neural message passing on a graph, consisting of interacting atom verti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	205,219
2211.04972	Hibikino-Musashi@Home 2018 Team Description Paper	Our team, Hibikino-Musashi@Home (the shortened name is HMA), was founded in 2010. It is based in the Kitakyushu Science and Research Park, Japan. We have participated in the RoboCup@Home Japan open competition open platform league every year since 2010. Moreover, we participated in the RoboCup 2017 Nagoya as open platf...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	329,402
2301.13142	Self-Compressing Neural Networks	This work focuses on reducing neural network size, which is a major driver of neural network execution time, power consumption, bandwidth, and memory footprint. A key challenge is to reduce size in a manner that can be exploited readily for efficient training and inference without the need for specialized hardware. We ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	342,797
2312.06457	Large Language Models with Retrieval-Augmented Generation for Zero-Shot Disease Phenotyping	Identifying disease phenotypes from electronic health records (EHRs) is critical for numerous secondary uses. Manually encoding physician knowledge into rules is particularly challenging for rare diseases due to inadequate EHR coding, necessitating review of clinical notes. Large language models (LLMs) offer promise in...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	414,526
2202.03045	Metric-valued regression	We propose an efficient algorithm for learning mappings between two metric spaces, $\X$ and $\Y$. Our procedure is strongly Bayes-consistent whenever $\X$ and $\Y$ are topologically separable and $\Y$ is "bounded in expectation" (our term; the separability assumption can be somewhat weakened). At this level of generali...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,052
2412.17487	DeepMF: Deep Motion Factorization for Closed-Loop Safety-Critical Driving Scenario Simulation	Safety-critical traffic scenarios are of great practical relevance to evaluating the robustness of autonomous driving (AD) systems. Given that these long-tail events are extremely rare in real-world traffic data, there is a growing body of work dedicated to the automatic traffic scenario generation. However, nearly all...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	519,995
2404.16514	Adaptive Learning-based Model Predictive Control for Uncertain Interconnected Systems: A Set Membership Identification Approach	We propose a novel adaptive learning-based model predictive control (MPC) scheme for interconnected systems which can be decomposed into several smaller dynamically coupled subsystems with uncertain coupling. The proposed scheme is mainly divided into two main online phases; a learning phase and an adaptation phase. Se...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	449,526
1810.03278	Optimizing Waiting Thresholds Within A State Machine	Azure (the cloud service provided by Microsoft) is composed of physical computing units which are called nodes. These nodes are controlled by a software component called Fabric Controller (FC), which can consider the nodes to be in one of many different states such as Ready, Unhealthy, Booting, etc. Some of these state...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	109,777
2212.06868	Deep Image Style Transfer from Freeform Text	This paper creates a novel method of deep neural style transfer by generating style images from freeform user text input. The language model and style transfer model form a seamless pipeline that can create output images with similar losses and improved quality when compared to baseline style transfer methods. The lang...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	336,234
2409.03634	Surface-Centric Modeling for High-Fidelity Generalizable Neural Surface Reconstruction	Reconstructing the high-fidelity surface from multi-view images, especially sparse images, is a critical and practical task that has attracted widespread attention in recent years. However, existing methods are impeded by the memory constraint or the requirement of ground-truth depths and cannot recover satisfactory ge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	486,110
1704.00651	Fast Encoding and Decoding of Flexible-Rate and Flexible-Length Polar Codes	This work is on fast encoding and decoding of polar codes. We propose and detail 8-bit and 16-bit parallel decoders that can be used to reduce the decoding latency of the successive-cancellation decoder. These decoders are universal and can decode flexible-rate and flexible-length polar codes. We also present fast enco...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	71,121
2010.10007	A Simple Baseline for Pose Tracking in Videos of Crowded Scenes	This paper presents our solution to ACM MM challenge: Large-scale Human-centric Video Analysis in Complex Events\cite{lin2020human}; specifically, here we focus on Track3: Crowd Pose Tracking in Complex Events. Remarkable progress has been made in multi-pose training in recent years. However, how to track the human pos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	201,744
1709.02232	RNN-based Early Cyber-Attack Detection for the Tennessee Eastman Process	An RNN-based forecasting approach is used to early detect anomalies in industrial multivariate time series data from a simulated Tennessee Eastman Process (TEP) with many cyber-attacks. This work continues a previously proposed LSTM-based approach to the fault detection in simpler data. It is considered necessary to ad...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	80,221
2111.05034	Classifying DNS Servers based on Response Message Matrix using Machine Learning	Improperly configured domain name system (DNS) servers are sometimes used as packet reflectors as part of a DoS or DDoS attack. Detecting packets created as a result of this activity is logically possible by monitoring the DNS request and response traffic. Any response that does not have a corresponding request can be ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	265,678
2108.11305	CSG-Stump: A Learning Friendly CSG-Like Representation for Interpretable Shape Parsing	Generating an interpretable and compact representation of 3D shapes from point clouds is an important and challenging problem. This paper presents CSG-Stump Net, an unsupervised end-to-end network for learning shapes from point clouds and discovering the underlying constituent modeling primitives and operations as well...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	252,146
2005.03286	Multi-view data capture using edge-synchronised mobiles	Multi-view data capture permits free-viewpoint video (FVV) content creation. To this end, several users must capture video streams, calibrated in both time and pose, framing the same object/scene, from different viewpoints. New-generation network architectures (e.g. 5G) promise lower latency and larger bandwidth connec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	176,113
2205.12152	Performance analysis of downlink MIMO-NOMA systems over Weibull fading channels	This work analyzes the performance of a downlink multi-user multiple-input multiple-output (MU-MIMO) non-orthogonal multiple access (NOMA) communications system. To reduce hardware complexity and exploit antenna diversity, we consider a transmit antenna selection (TAS) scheme and equal-gain combining (EGC) receivers. F...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	298,421
1412.5448	Extended Recommendation Framework: Generating the Text of a User Review as a Personalized Summary	We propose to augment rating based recommender systems by providing the user with additional information which might help him in his choice or in the understanding of the recommendation. We consider here as a new task, the generation of personalized reviews associated to items. We use an extractive summary formulation ...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	38,488
1701.07393	Recovering 3D Planar Arrangements from Videos	Acquiring 3D geometry of real world objects has various applications in 3D digitization, such as navigation and content generation in virtual environments. Image remains one of the most popular media for such visual tasks due to its simplicity of acquisition. Traditional image-based 3D reconstruction approaches heavily...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	67,278
1704.06726	Distant Supervision for Topic Classification of Tweets in Curated Streams	We tackle the challenge of topic classification of tweets in the context of analyzing a large collection of curated streams by news outlets and other organizations to deliver relevant content to users. Our approach is novel in applying distant supervision based on semi-automatically identifying curated streams that are...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	72,209
2006.08600	Temporal Phenotyping using Deep Predictive Clustering of Disease Progression	Due to the wider availability of modern electronic health records, patient care data is often being stored in the form of time-series. Clustering such time-series data is crucial for patient phenotyping, anticipating patients' prognoses by identifying "similar" patients, and designing treatment guidelines that are tail...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,241
2405.17329	Joint MIMO Transceiver and Reflector Design for Reconfigurable Intelligent Surface-Assisted Communication	In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted multiple-input multiple-output communication system with multiple antennas at both the base station (BS) and the user. We plan to maximize the achievable rate through jointly optimizing the transmit precoding matrix, the receive combining ma...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	457,858
1201.5227	A New Local Adaptive Thresholding Technique in Binarization	Image binarization is the process of separation of pixel values into two groups, white as background and black as foreground. Thresholding plays a major in binarization of images. Thresholding can be categorized into global thresholding and local thresholding. In images with uniform contrast distribution of background ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	13,950
2010.09920	Optimality vs Stability Trade-off in Ensemble Kalman Filters	This paper is concerned with optimality and stability analysis of a family of ensemble Kalman filter (EnKF) algorithms. EnKF is commonly used as an alternative to the Kalman filter for high-dimensional problems, where storing the covariance matrix is computationally expensive. The algorithm consists of an ensemble of i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	201,704
1806.08236	Learning Transposition-Invariant Interval Features from Symbolic Music and Audio	Many music theoretical constructs (such as scale types, modes, cadences, and chord types) are defined in terms of pitch intervals---relative distances between pitches. Therefore, when computer models are employed in music tasks, it can be useful to operate on interval representations rather than on the raw musical surf...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	101,119
2407.11372	UNIT: Backdoor Mitigation via Automated Neural Distribution Tightening	Deep neural networks (DNNs) have demonstrated effectiveness in various fields. However, DNNs are vulnerable to backdoor attacks, which inject a unique pattern, called trigger, into the input to cause misclassification to an attack-chosen target label. While existing works have proposed various methods to mitigate backd...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	473,418
1604.04967	On recovering missing values for sequences in a pathwise setting	The paper suggests a frequency criterion of error-free recoverability of a missing value for sequences, i.e. discrete time processes, in a pathwise setting without probabilistic assumptions. The paper establishes error-free recoverability for classes of square-summable sequences with Z-transform vanishing at isolated p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	54,740
1909.01247	Introducing RONEC -- the Romanian Named Entity Corpus	We present RONEC - the Named Entity Corpus for the Romanian language. The corpus contains over 26000 entities in ~5000 annotated sentences, belonging to 16 distinct classes. The sentences have been extracted from a copy-right free newspaper, covering several styles. This corpus represents the first initiative in the Ro...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	143,857
1702.06027	Parent Oriented Teacher Selection Causes Language Diversity	An evolutionary model for emergence of diversity in language is developed. We investigated the effects of two real life observations, namely, people prefer people that they communicate with well, and people interact with people that are physically close to each other. Clearly these groups are relatively small compared ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	68,517
2101.08734	Clairvoyant Prefetching for Distributed Machine Learning I/O	I/O is emerging as a major bottleneck for machine learning training, especially in distributed environments. Indeed, at large scale, I/O takes as much as 85% of training time. Addressing this I/O bottleneck necessitates careful optimization, as optimal data ingestion pipelines differ between systems, and require a deli...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	216,402
2401.15206	Backscatter Measurements and Models for RF Sensing Applications in Cluttered Environments	A statistical backscatter channel model for indoor clutter is developed for indoor RF sensing applications based on measurements. A narrowband 28 GHz sounder used a quazi-monostatic radar arrangement with an omnidirectional transmit antenna illuminating an indoor scene and a spinning horn receive antenna less than 1 m ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	424,355
1511.06382	Iterative Refinement of the Approximate Posterior for Directed Belief Networks	Variational methods that rely on a recognition network to approximate the posterior of directed graphical models offer better inference and learning than previous methods. Recent advances that exploit the capacity and flexibility in this approach have expanded what kinds of models can be trained. However, as a proposal...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	49,217
1904.03579	Adaptively Connected Neural Networks	This paper presents a novel adaptively connected neural network (ACNet) to improve the traditional convolutional neural networks (CNNs) {in} two aspects. First, ACNet employs a flexible way to switch global and local inference in processing the internal feature representations by adaptively determining the connection s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,775
1711.08757	Deep Expander Networks: Efficient Deep Networks from Graph Theory	Efficient CNN designs like ResNets and DenseNet were proposed to improve accuracy vs efficiency trade-offs. They essentially increased the connectivity, allowing efficient information flow across layers. Inspired by these techniques, we propose to model connections between filters of a CNN using graphs which are simult...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,263
2210.11291	Cyclical Self-Supervision for Semi-Supervised Ejection Fraction Prediction from Echocardiogram Videos	Left-ventricular ejection fraction (LVEF) is an important indicator of heart failure. Existing methods for LVEF estimation from video require large amounts of annotated data to achieve high performance, e.g. using 10,030 labeled echocardiogram videos to achieve mean absolute error (MAE) of 4.10. Labeling these videos i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	325,262
1501.05005	Varentropy Decreases Under the Polar Transform	We consider the evolution of variance of entropy (varentropy) in the course of a polar transform operation on binary data elements (BDEs). A BDE is a pair $(X,Y)$ consisting of a binary random variable $X$ and an arbitrary side information random variable $Y$. The varentropy of $(X,Y)$ is defined as the variance of the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,440
2305.18618	Chatbots put to the test in math and logic problems: A preliminary comparison and assessment of ChatGPT-3.5, ChatGPT-4, and Google Bard	A comparison between three chatbots which are based on large language models, namely ChatGPT-3.5, ChatGPT-4 and Google Bard is presented, focusing on their ability to give correct answers to mathematics and logic problems. In particular, we check their ability to Understand the problem at hand; Apply appropriate algori...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	369,162
2004.04934	Scalable Multilingual Frontend for TTS	This paper describes progress towards making a Neural Text-to-Speech (TTS) Frontend that works for many languages and can be easily extended to new languages. We take a Machine Translation (MT) inspired approach to constructing the frontend, and model both text normalization and pronunciation on a sentence level by bui...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	172,037
2310.09298	ByteStack-ID: Integrated Stacked Model Leveraging Payload Byte Frequency for Grayscale Image-based Network Intrusion Detection	In the ever-evolving realm of network security, the swift and accurate identification of diverse attack classes within network traffic is of paramount importance. This paper introduces "ByteStack-ID," a pioneering approach tailored for packet-level intrusion detection. At its core, ByteStack-ID leverages grayscale imag...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	399,727
2107.10971	Adaptively Weighted Top-N Recommendation for Organ Matching	Reducing the shortage of organ donations to meet the demands of patients on the waiting list has being a major challenge in organ transplantation. Because of the shortage, organ matching decision is the most critical decision to assign the limited viable organs to the most suitable patients. Currently, organ matching d...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	247,448
1611.01850	On High-Resolution Adaptive Sampling of Deterministic Signals	In this work we study the topic of high-resolution adaptive sampling of a given deterministic signal and establish a connection with classic approaches to high-rate quantization. Specifically, we formulate solutions for the task of optimal high-resolution sampling, counterparts of well-known results for high-rate quant...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	63,452
2405.15113	A Wearable Resistance Devices Motor Learning Effects in Exercise	The integration of technology into exercise regimens has emerged as a strategy to enhance normal human capabilities and return human motor function after injury or illness by enhancing motor learning and retention. Much research has focused on how active devices, whether confined to a lab or made into a wearable format...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	456,750
2204.12446	Beyond Lipschitz: Sharp Generalization and Excess Risk Bounds for Full-Batch GD	We provide sharp path-dependent generalization and excess risk guarantees for the full-batch Gradient Descent (GD) algorithm on smooth losses (possibly non-Lipschitz, possibly nonconvex). At the heart of our analysis is an upper bound on the generalization error, which implies that average output stability and a bounde...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	293,478
1902.10770	Learning Task Knowledge and its Scope of Applicability in Experience-Based Planning Domains	Experience-based planning domains (EBPDs) have been recently proposed to improve problem solving by learning from experience. EBPDs provide important concepts for long-term learning and planning in robotics. They rely on acquiring and using task knowledge, i.e., activity schemata, for generating concrete solutions to p...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	122,766
1608.02201	Residual CNDS	Convolutional Neural networks nowadays are of tremendous importance for any image classification system. One of the most investigated methods to increase the accuracy of CNN is by increasing the depth of CNN. Increasing the depth by stacking more layers also increases the difficulty of training besides making it comput...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,529
cs/0204044	Robust Global Localization Using Clustered Particle Filtering	Global mobile robot localization is the problem of determining a robot's pose in an environment, using sensor data, when the starting position is unknown. A family of probabilistic algorithms known as Monte Carlo Localization (MCL) is currently among the most popular methods for solving this problem. MCL algorithms rep...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	537,556
2502.09897	Artificial Intelligence in Spectroscopy: Advancing Chemistry from Prediction to Generation and Beyond	The rapid advent of machine learning (ML) and artificial intelligence (AI) has catalyzed major transformations in chemistry, yet the application of these methods to spectroscopic and spectrometric data, referred to as Spectroscopy Machine Learning (SpectraML), remains relatively underexplored. Modern spectroscopic tech...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	533,650
2407.00710	Directly Handling Missing Data in Linear Discriminant Analysis for Enhancing Classification Accuracy and Interpretability	As the adoption of Artificial Intelligence (AI) models expands into critical real-world applications, ensuring the explainability of these models becomes paramount, particularly in sensitive fields such as medicine and finance. Linear Discriminant Analysis (LDA) remains a popular choice for classification due to its in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	468,979
2402.03969	In-context learning agents are asymmetric belief updaters	We study the in-context learning dynamics of large language models (LLMs) using three instrumental learning tasks adapted from cognitive psychology. We find that LLMs update their beliefs in an asymmetric manner and learn more from better-than-expected outcomes than from worse-than-expected ones. Furthermore, we show t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	427,274
0910.5027	Information-theoretically Secret Key Generation for Fading Wireless Channels	The multipath-rich wireless environment associated with typical wireless usage scenarios is characterized by a fading channel response that is time-varying, location-sensitive, and uniquely shared by a given transmitter-receiver pair. The complexity associated with a richly scattering environment implies that the short...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	4,804
2305.05402	Consistent Text Categorization using Data Augmentation in e-Commerce	The categorization of massive e-Commerce data is a crucial, well-studied task, which is prevalent in industrial settings. In this work, we aim to improve an existing product categorization model that is already in use by a major web company, serving multiple applications. At its core, the product categorization model i...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	363,136
1311.2637	Self-Dual codes from $(-1,1)$-matrices of skew symmetric type	Previously, self-dual codes have been constructed from weighing matrices, and in particular from conference matrices (skew and symmetric). In this paper, codes constructed from matrices of skew symmetric type whose determinants reach the Ehlich-Wojtas' bound are presented. A necessary and sufficient condition for these...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	28,337
2404.11817	Reinforcement Learning of Multi-robot Task Allocation for Multi-object Transportation with Infeasible Tasks	Multi-object transport using multi-robot systems has the potential for diverse practical applications such as delivery services owing to its efficient individual and scalable cooperative transport. However, allocating transportation tasks of objects with unknown weights remains challenging. Moreover, the presence of in...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	447,623
1408.2042	Gaussian Process Structural Equation Models with Latent Variables	In a variety of disciplines such as social sciences, psychology, medicine and economics, the recorded data are considered to be noisy measurements of latent variables connected by some causal structure. This corresponds to a family of graphical models known as the structural equation model with latent variables. While ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	35,241
2406.03726	Efficient Graph Encoder Embedding for Large Sparse Graphs in Python	Graph is a ubiquitous representation of data in various research fields, and graph embedding is a prevalent machine learning technique for capturing key features and generating fixed-sized attributes. However, most state-of-the-art graph embedding methods are computationally and spatially expensive. Recently, the Graph...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	461,362
2007.08690	Transfer Deep Reinforcement Learning-enabled Energy Management Strategy for Hybrid Tracked Vehicle	This paper proposes an adaptive energy management strategy for hybrid electric vehicles by combining deep reinforcement learning (DRL) and transfer learning (TL). This work aims to address the defect of DRL in tedious training time. First, an optimization control modeling of a hybrid tracked vehicle is built, wherein t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	187,708
2411.16145	Local Intrinsic Dimensionality for Dynamic Graph Embeddings	The notion of local intrinsic dimensionality (LID) has important theoretical implications and practical applications in the fields of data mining and machine learning. Recent research efforts indicate that LID measures defined for graphs can improve graph representational learning methods based on random walks. In this...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	510,916
2108.11637	Self-Attention for Audio Super-Resolution	Convolutions operate only locally, thus failing to model global interactions. Self-attention is, however, able to learn representations that capture long-range dependencies in sequences. We propose a network architecture for audio super-resolution that combines convolution and self-attention. Attention-based Feature-Wi...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	252,236
2401.12235	Stochastic Dynamic Power Dispatch with High Generalization and Few-Shot Adaption via Contextual Meta Graph Reinforcement Learning	Reinforcement learning is an emerging approaches to facilitate multi-stage sequential decision-making problems. This paper studies a real-time multi-stage stochastic power dispatch considering multivariate uncertainties. Current researches suffer from low generalization and practicality, that is, the learned dispatch p...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	423,309
2306.08010	Domain Information Control at Inference Time for Acoustic Scene Classification	Domain shift is considered a challenge in machine learning as it causes significant degradation of model performance. In the Acoustic Scene Classification task (ASC), domain shift is mainly caused by different recording devices. Several studies have already targeted domain generalization to improve the performance of A...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	373,254
2301.00633	Nested perfect toroidal arrays	We introduce two-dimensional toroidal arrays that are a variant of the de Bruijn tori. We call them nested perfect toroidal arrays. Instead of asking that every array of a given size has exactly one occurrence, we partition the positions in congruence classes and we ask exactly one occurrence in each congruence class. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	338,971
2309.00296	End-to-end Lidar-Driven Reinforcement Learning for Autonomous Racing	Reinforcement Learning (RL) has emerged as a transformative approach in the domains of automation and robotics, offering powerful solutions to complex problems that conventional methods struggle to address. In scenarios where the problem definitions are elusive and challenging to quantify, learning-based solutions such...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	389,257
1305.0983	Real-Time Welfare-Maximizing Regulation Allocation in Dynamic Aggregator-EVs System	The concept of vehicle-to-grid (V2G) has gained recent interest as more and more electric vehicles (EVs) are put to use. In this paper, we consider a dynamic aggregator-EVs system, where an aggregator centrally coordinates a large number of dynamic EVs to perform regulation service. We propose a Welfare-Maximizing Regu...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	24,394

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