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
2403.15800	MRC-based Nested Medical NER with Co-prediction and Adaptive Pre-training	In medical information extraction, medical Named Entity Recognition (NER) is indispensable, playing a crucial role in developing medical knowledge graphs, enhancing medical question-answering systems, and analyzing electronic medical records. The challenge in medical NER arises from the complex nested structures and so...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	440,752
2302.14704	Joint Spectrum and Power Allocation for V2X Communications with Imperfect CSI	In Vehicle-to-Everything (V2X) communication, the high mobility of vehicles generates the Doppler shift which leads to channel uncertainties. Moreover, the reasons for channel uncertainties also include the finite channel feedback, channels state information (CSI) loss and latency. With this concern, we formulate a joi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	348,404
2002.00336	3D Object Detection on Point Clouds using Local Ground-aware and Adaptive Representation of scenes' surface	A novel, adaptive ground-aware, and cost-effective 3D Object Detection pipeline is proposed. The ground surface representation introduced in this paper, in comparison to its uni-planar counterparts (methods that model the surface of a whole 3D scene using single plane), is far more accurate while being ~10x faster. The...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	162,328
2301.08590	Improving Sketch Colorization using Adversarial Segmentation Consistency	We propose a new method for producing color images from sketches. Current solutions in sketch colorization either necessitate additional user instruction or are restricted to the "paired" translation strategy. We leverage semantic image segmentation from a general-purpose panoptic segmentation network to generate an ad...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	341,240
1601.02216	Physical Layer Security in Three-Tier Wireless Sensor Networks: A Stochastic Geometry Approach	This paper develops a tractable framework for exploiting the potential benefits of physical layer security in three-tier wireless sensor networks using stochastic geometry. In such networks, the sensing data from the remote sensors are collected by sinks with the help of access points, and the external eavesdroppers in...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	50,811
2404.11581	LLMTune: Accelerate Database Knob Tuning with Large Language Models	Database knob tuning is a critical challenge in the database community, aiming to optimize knob values to enhance database performance for specific workloads. DBMS often feature hundreds of tunable knobs, posing a significant challenge for DBAs to recommend optimal configurations. Consequently, many machine learning-ba...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	447,546
2101.03279	Investigating the Effect of Sensor Modalities in Multi-Sensor Detection-Prediction Models	Detection of surrounding objects and their motion prediction are critical components of a self-driving system. Recently proposed models that jointly address these tasks rely on a number of sensors to achieve state-of-the-art performance. However, this increases system complexity and may result in a brittle model that o...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	214,877
2410.23128	Leader-Follower 3D Formation for Underwater Robots	The schooling behavior of fish is hypothesized to confer many survival benefits, including foraging success, safety from predators, and energy savings through hydrodynamic interactions when swimming in formation. Underwater robot collectives may be able to achieve similar benefits in future applications, e.g. using for...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	503,911
2202.09813	Real-time Emotion Appraisal with Circumplex Model for Human-Robot Interaction	Emotions are the intrinsic or extrinsic representations of our experiences. The importance of emotions during a human-human interaction is immense as it formulates the basis of our interaction framework. There are several approaches in psychology to evaluate emotional states in humans based on the perceived stimuli. Ho...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	281,327
1102.1480	Joint Decoding of LDPC Codes and Finite-State Channels via Linear-Programming	This paper considers the joint-decoding (JD) problem for finite-state channels (FSCs) and low-density parity-check (LDPC) codes. In the first part, the linear-programming (LP) decoder for binary linear codes is extended to JD of binary-input FSCs. In particular, we provide a rigorous definition of LP joint-decoding pse...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	9,071
2404.07292	Solving Masked Jigsaw Puzzles with Diffusion Vision Transformers	Solving image and video jigsaw puzzles poses the challenging task of rearranging image fragments or video frames from unordered sequences to restore meaningful images and video sequences. Existing approaches often hinge on discriminative models tasked with predicting either the absolute positions of puzzle elements or ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,786
2403.17599	Coimagining the Future of Voice Assistants with Cultural Sensitivity	Voice assistants (VAs) are becoming a feature of our everyday life. Yet, the user experience (UX) is often limited, leading to underuse, disengagement, and abandonment. Co-designing interactions for VAs with potential end-users can be useful. Crowdsourcing this process online and anonymously may add value. However, mos...	true	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	441,533
2211.14928	Class-based Quantization for Neural Networks	In deep neural networks (DNNs), there are a huge number of weights and multiply-and-accumulate (MAC) operations. Accordingly, it is challenging to apply DNNs on resource-constrained platforms, e.g., mobile phones. Quantization is a method to reduce the size and the computational complexity of DNNs. Existing quantizatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	333,048
2307.06362	Spectral-Bias and Kernel-Task Alignment in Physically Informed Neural Networks	Physically informed neural networks (PINNs) are a promising emerging method for solving differential equations. As in many other deep learning approaches, the choice of PINN design and training protocol requires careful craftsmanship. Here, we suggest a comprehensive theoretical framework that sheds light on this impor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	379,046
2311.10809	Extracting periodontitis diagnosis in clinical notes with RoBERTa and regular expression	This study aimed to utilize text processing and natural language processing (NLP) models to mine clinical notes for the diagnosis of periodontitis and to evaluate the performance of a named entity recognition (NER) model on different regular expression (RE) methods. Two complexity levels of RE methods were used to extr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	408,679
2007.01758	Collaborative Learning for Faster StyleGAN Embedding	The latent code of the recent popular model StyleGAN has learned disentangled representations thanks to the multi-layer style-based generator. Embedding a given image back to the latent space of StyleGAN enables wide interesting semantic image editing applications. Although previous works are able to yield impressive i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	185,523
2408.09818	Liquid Fourier Latent Dynamics Networks for fast GPU-based numerical simulations in computational cardiology	Scientific Machine Learning (ML) is gaining momentum as a cost-effective alternative to physics-based numerical solvers in many engineering applications. In fact, scientific ML is currently being used to build accurate and efficient surrogate models starting from high-fidelity numerical simulations, effectively encodin...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	481,601
2006.15975	Robots and COVID-19: Challenges in integrating robots for collaborative automation	Objective: The status of human-robot collaboration for assembly applications is reviewed and key current challenges for the research community and practitioners are presented. Background: As the pandemic of COVID-19 started to surface the manufacturers went under pressure to address demand challenges. Social distancing...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	184,676
2112.14820	Application of Hierarchical Temporal Memory Theory for Document Categorization	The current work intends to study the performance of the Hierarchical Temporal Memory(HTM) theory for automated classification of text as well as documents. HTM is a biologically inspired theory based on the working principles of the human neocortex. The current study intends to provide an alternative framework for doc...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	273,620
2410.10481	Model-Based Privacy-Preserving Knowledge Transfer for Large Language Models	As large language models (LLMs) become more prevalent, effectively utilizing domain-specific knowledge while ensuring privacy has become critical. Existing methods often struggle to balance utility and privacy. For instance, retrieval-augmented generation (RAG) enables LLMs to access domain-specific knowledge but compr...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	498,097
1810.12138	Audio inpainting of music by means of neural networks	We studied the ability of deep neural networks (DNNs) to restore missing audio content based on its context, a process usually referred to as audio inpainting. We focused on gaps in the range of tens of milliseconds. The proposed DNN structure was trained on audio signals containing music and musical instruments, separ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	111,691
2208.00767	Multimodal Neural Machine Translation with Search Engine Based Image Retrieval	Recently, numbers of works shows that the performance of neural machine translation (NMT) can be improved to a certain extent with using visual information. However, most of these conclusions are drawn from the analysis of experimental results based on a limited set of bilingual sentence-image pairs, such as Multi30K. ...	false	false	false	false	true	true	false	false	true	false	false	true	false	false	false	false	false	false	310,955
1711.09744	How linguistic descriptions of data can help to the teaching-learning process in higher education, case of study: artificial intelligence	Artificial Intelligence is a central topic in the computer science curriculum. From the year 2011 a project-based learning methodology based on computer games has been designed and implemented into the intelligence artificial course at the University of the Bio-Bio. The project aims to develop software-controlled agent...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	85,467
2310.10301	Multi-Body Neural Scene Flow	The test-time optimization of scene flow - using a coordinate network as a neural prior - has gained popularity due to its simplicity, lack of dataset bias, and state-of-the-art performance. We observe, however, that although coordinate networks capture general motions by implicitly regularizing the scene flow predicti...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	400,166
2406.12334	What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering	Large Language Models (LLMs) changed the way we design and interact with software systems. Their ability to process and extract information from text has drastically improved productivity in a number of routine tasks. Developers that want to include these models in their software stack, however, face a dreadful challen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	465,349
2412.15298	A Comparative Study of DSPy Teleprompter Algorithms for Aligning Large Language Models Evaluation Metrics to Human Evaluation	We argue that the Declarative Self-improving Python (DSPy) optimizers are a way to align the large language model (LLM) prompts and their evaluations to the human annotations. We present a comparative analysis of five teleprompter algorithms, namely, Cooperative Prompt Optimization (COPRO), Multi-Stage Instruction Prom...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	519,050
2205.15413	PolypConnect: Image inpainting for generating realistic gastrointestinal tract images with polyps	Early identification of a polyp in the lower gastrointestinal (GI) tract can lead to prevention of life-threatening colorectal cancer. Developing computer-aided diagnosis (CAD) systems to detect polyps can improve detection accuracy and efficiency and save the time of the domain experts called endoscopists. Lack of ann...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	299,712
1609.00651	Safety Barrier Certificates for Heterogeneous Multi-Robot Systems	This paper presents a formal framework for collision avoidance in multi-robot systems, wherein an existing controller is modified in a minimally invasive fashion to ensure safety. We build this framework through the use of control barrier functions (CBFs) which guarantee forward invariance of a safe set; these yield sa...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	60,502
1409.8112	Efficient high-quality motion planning by fast all-pairs r-nearest-neighbors	Sampling-based motion-planning algorithms typically rely on nearest-neighbor (NN) queries when constructing a roadmap. Recent results suggest that in various settings NN queries may be the computational bottleneck of such algorithms. Moreover, in several asymptotically-optimal algorithms these NN queries are of a speci...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	36,385
2405.19735	Twin Deformable Point Convolutions for Point Cloud Semantic Segmentation in Remote Sensing Scenes	Thanks to the application of deep learning technology in point cloud processing of the remote sensing field, point cloud segmentation has become a research hotspot in recent years, which can be applied to real-world 3D, smart cities, and other fields. Although existing solutions have made unprecedented progress, they i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	459,037
2412.19755	"Did my figure do justice to the answer?" : Towards Multimodal Short Answer Grading with Feedback (MMSAF)	Assessments play a vital role in a student's learning process by providing feedback on a student's proficiency level in a subject. While assessments often make use of short answer questions, it is often difficult to grade such questions at a large scale. Moreover, such questions often involve students drawing supportin...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	520,956
2109.04689	Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation Learning	Motivated by suggested question generation in conversational news recommendation systems, we propose a model for generating question-answer pairs (QA pairs) with self-contained, summary-centric questions and length-constrained, article-summarizing answers. We begin by collecting a new dataset of news articles with ques...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	254,498
2308.15556	Polarized Speech on Online Platforms in the American Political Context	Using language models, we analyze approximately 2.5 billion comments from Reddit and Twitter across 1.7 million accounts spanning 2007 to 2023 to study the prevalence and evolution of polarized rhetoric in American political discourse. Our findings show rising outgroup polarization on both platforms, with each new coho...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	388,718
0708.2213	Moderate Growth Time Series for Dynamic Combinatorics Modelisation	Here, we present a family of time series with a simple growth constraint. This family can be the basis of a model to apply to emerging computation in business and micro-economy where global functions can be expressed from local rules. We explicit a double statistics on these series which allows to establish a one-to-on...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	557
2405.18937	Kestrel: Point Grounding Multimodal LLM for Part-Aware 3D Vision-Language Understanding	While 3D MLLMs have achieved significant progress, they are restricted to object and scene understanding and struggle to understand 3D spatial structures at the part level. In this paper, we introduce Kestrel, representing a novel approach that empowers 3D MLLMs with part-aware understanding, enabling better interpreta...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	458,676
1802.10474	On the Benefits of Asymmetric Coded Cache Placement in Combination Networks with End-User Caches	This paper investigates the fundamental tradeoff between cache size and download time in the (H;r;M;N) combination network, where a server with N files is connected to H relays (without caches) and each of the K:=\binom{H}{r} users (with caches of size M files) is connected to a different subset of r relays. Existing s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	91,532
2210.14510	Multi-Environment based Meta-Learning with CSI Fingerprints for Radio Based Positioning	Radio based positioning of a user equipment (UE) based on deep learning (DL) methods using channel state information (CSI) fingerprints have shown promising results. DL models are able to capture complex properties embedded in the CSI about a particular environment and map UE's CSI to the UE's position. However, the CS...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	326,578
2403.09307	Annotation Free Semantic Segmentation with Vision Foundation Models	Semantic Segmentation is one of the most challenging vision tasks, usually requiring large amounts of training data with expensive pixel level annotations. With the success of foundation models and especially vision-language models, recent works attempt to achieve zeroshot semantic segmentation while requiring either l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	437,716
2208.14167	Synthehicle: Multi-Vehicle Multi-Camera Tracking in Virtual Cities	Smart City applications such as intelligent traffic routing or accident prevention rely on computer vision methods for exact vehicle localization and tracking. Due to the scarcity of accurately labeled data, detecting and tracking vehicles in 3D from multiple cameras proves challenging to explore. We present a massive ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	315,242
2407.19332	A Semi-supervised Fake News Detection using Sentiment Encoding and LSTM with Self-Attention	Micro-blogs and cyber-space social networks are the main communication mediums to receive and share news nowadays. As a side effect, however, the networks can disseminate fake news that harms individuals and the society. Several methods have been developed to detect fake news, but the majority require large sets of man...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	476,743
2011.00747	Dual-decoder Transformer for Joint Automatic Speech Recognition and Multilingual Speech Translation	We introduce dual-decoder Transformer, a new model architecture that jointly performs automatic speech recognition (ASR) and multilingual speech translation (ST). Our models are based on the original Transformer architecture (Vaswani et al., 2017) but consist of two decoders, each responsible for one task (ASR or ST). ...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	204,349
2203.06605	Depth-Aware Generative Adversarial Network for Talking Head Video Generation	Talking head video generation aims to produce a synthetic human face video that contains the identity and pose information respectively from a given source image and a driving video.Existing works for this task heavily rely on 2D representations (e.g. appearance and motion) learned from the input images. However, dense...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,171
2012.01359	3D architected isotropic materials with tunable stiffness and buckling strength	This paper presents a class of 3D single-scale isotropic materials with tunable stiffness and buckling strength obtained via topology optimization and subsequent shape optimization. Compared to stiffness-optimal closed-cell plate material, the material class reduces the Young's modulus to a range from 79% to 58%, but i...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	209,396
2307.16169	StarSRGAN: Improving Real-World Blind Super-Resolution	The aim of blind super-resolution (SR) in computer vision is to improve the resolution of an image without prior knowledge of the degradation process that caused the image to be low-resolution. The State of the Art (SOTA) model Real-ESRGAN has advanced perceptual loss and produced visually compelling outcomes using mor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	382,499
2110.09267	Boosting Image Outpainting with Semantic Layout Prediction	The objective of image outpainting is to extend image current border and generate new regions based on known ones. Previous methods adopt generative adversarial networks (GANs) to synthesize realistic images. However, the lack of explicit semantic representation leads to blurry and abnormal image pixels when the outpai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	261,748
1906.09340	Leveraging Reinforcement Learning Techniques for Effective Policy Adoption and Validation	Rewards and punishments in different forms are pervasive and present in a wide variety of decision-making scenarios. By observing the outcome of a sufficient number of repeated trials, one would gradually learn the value and usefulness of a particular policy or strategy. However, in a given environment, the outcomes re...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	136,126
2310.07018	NEWTON: Are Large Language Models Capable of Physical Reasoning?	Large Language Models (LLMs), through their contextualized representations, have been empirically proven to encapsulate syntactic, semantic, word sense, and common-sense knowledge. However, there has been limited exploration of their physical reasoning abilities, specifically concerning the crucial attributes for compr...	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	398,795
2405.10046	A Preprocessing and Postprocessing Voxel-based Method for LiDAR Semantic Segmentation Improvement in Long Distance	In recent years considerable research in LiDAR semantic segmentation was conducted, introducing several new state of the art models. However, most research focuses on single-scan point clouds, limiting performance especially in long distance outdoor scenarios, by omitting time-sequential information. Moreover, varying-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	454,631
2304.12130	Reconstructing Turbulent Flows Using Physics-Aware Spatio-Temporal Dynamics and Test-Time Refinement	Simulating turbulence is critical for many societally important applications in aerospace engineering, environmental science, the energy industry, and biomedicine. Large eddy simulation (LES) has been widely used as an alternative to direct numerical simulation (DNS) for simulating turbulent flows due to its reduced co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	360,090
1710.09288	Adversarial Deep Structured Nets for Mass Segmentation from Mammograms	Mass segmentation provides effective morphological features which are important for mass diagnosis. In this work, we propose a novel end-to-end network for mammographic mass segmentation which employs a fully convolutional network (FCN) to model a potential function, followed by a CRF to perform structured learning. Be...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	83,183
1705.08620	Robust Data Geometric Structure Aligned Close yet Discriminative Domain Adaptation	Domain adaptation (DA) is transfer learning which aims to leverage labeled data in a related source domain to achieve informed knowledge transfer and help the classification of unlabeled data in a target domain. In this paper, we propose a novel DA method, namely Robust Data Geometric Structure Aligned, Close yet Discr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	74,057
2401.05412	Spatial-Related Sensors Matters: 3D Human Motion Reconstruction Assisted with Textual Semantics	Leveraging wearable devices for motion reconstruction has emerged as an economical and viable technique. Certain methodologies employ sparse Inertial Measurement Units (IMUs) on the human body and harness data-driven strategies to model human poses. However, the reconstruction of motion based solely on sparse IMUs data...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	420,771
1904.05276	Advances in Natural Language Question Answering: A Review	Question Answering has recently received high attention from artificial intelligence communities due to the advancements in learning technologies. Early question answering models used rule-based approaches and moved to the statistical approach to address the vastly available information. However, statistical approaches...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	127,261
2310.10688	A decoder-only foundation model for time-series forecasting	Motivated by recent advances in large language models for Natural Language Processing (NLP), we design a time-series foundation model for forecasting whose out-of-the-box zero-shot performance on a variety of public datasets comes close to the accuracy of state-of-the-art supervised forecasting models for each individu...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	400,347
2412.14846	Head and Neck Tumor Segmentation of MRI from Pre- and Mid-radiotherapy with Pre-training, Data Augmentation and Dual Flow UNet	Head and neck tumors and metastatic lymph nodes are crucial for treatment planning and prognostic analysis. Accurate segmentation and quantitative analysis of these structures require pixel-level annotation, making automated segmentation techniques essential for the diagnosis and treatment of head and neck cancer. In t...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	518,879
2303.07143	Multi-Microphone Speaker Separation by Spatial Regions	We consider the task of region-based source separation of reverberant multi-microphone recordings. We assume pre-defined spatial regions with a single active source per region. The objective is to estimate the signals from the individual spatial regions as captured by a reference microphone while retaining a correspond...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	351,138
2211.16126	Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting	Sensors in cyber-physical systems often capture interconnected processes and thus emit correlated time series (CTS), the forecasting of which enables important applications. The key to successful CTS forecasting is to uncover the temporal dynamics of time series and the spatial correlations among time series. Deep lear...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	333,525
2008.00190	On Supervised Classification of Feature Vectors with Independent and Non-Identically Distributed Elements	In this paper, we investigate the problem of classifying feature vectors with mutually independent but non-identically distributed elements. First, we show the importance of this problem. Next, we propose a classifier and derive an analytical upper bound on its error probability. We show that the error probability goes...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	189,935
1602.07109	Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series	Approximate variational inference has shown to be a powerful tool for modeling unknown complex probability distributions. Recent advances in the field allow us to learn probabilistic models of sequences that actively exploit spatial and temporal structure. We apply a Stochastic Recurrent Network (STORN) to learn robot ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	52,469
2411.14421	From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption	Accurate short-term energy consumption forecasting for commercial buildings is crucial for smart grid operations. While smart meters and deep learning models enable forecasting using past data from multiple buildings, data heterogeneity from diverse buildings can reduce model performance. The impact of increasing datas...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	510,151
2211.10248	Circuit Design for Predictive Maintenance	Industry 4.0 has become a driver for the entire manufacturing industry. Smart systems have enabled 30% productivity increases and predictive maintenance has been demonstrated to provide a 50% reduction in machine downtime. So far, the solution has been based on data analytics which has resulted in a proliferation of se...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	331,248
1408.3458	Stochastic Throughput Optimization for Two-hop Systems with Finite Relay Buffers	Optimal queueing control of multi-hop networks remains a challenging problem even in the simplest scenarios. In this paper, we consider a two-hop half-duplex relaying system with random channel connectivity. The relay is equipped with a finite buffer. We focus on stochastic link selection and transmission rate control ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	35,377
2311.10042	Depth Insight -- Contribution of Different Features to Indoor Single-image Depth Estimation	Depth estimation from a single image is a challenging problem in computer vision because binocular disparity or motion information is absent. Whereas impressive performances have been reported in this area recently using end-to-end trained deep neural architectures, as to what cues in the images that are being exploite...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,394
2312.06531	Uncertainty quantification in automated valuation models with spatially weighted conformal prediction	Non-parametric machine learning models, such as random forests and gradient boosted trees, are frequently used to estimate house prices due to their predictive accuracy, but a main drawback of such methods is their limited ability to quantify prediction uncertainty. Conformal prediction (CP) is a model-agnostic framewo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	414,554
2205.04424	Accelerated Reinforcement Learning for Temporal Logic Control Objectives	This paper addresses the problem of learning control policies for mobile robots, modeled as unknown Markov Decision Processes (MDPs), that are tasked with temporal logic missions, such as sequencing, coverage, or surveillance. The MDP captures uncertainty in the workspace structure and the outcomes of control decisions...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	295,635
2109.01229	Multimodal Conditionality for Natural Language Generation	Large scale pretrained language models have demonstrated state-of-the-art performance in language understanding tasks. Their application has recently expanded into multimodality learning, leading to improved representations combining vision and language. However, progress in adapting language models towards conditional...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	253,372
1610.05058	Local and global analysis of endocrine regulation as a non-cyclic feedback system	To understand the sophisticated control mechanisms of the human's endocrine system is a challenging task that is a crucial step towards precise medical treatment of many disfunctions and diseases. Although mathematical models describing the endocrine system as a whole are still elusive, recently some substantial progre...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	62,474
0906.0434	Total Variation, Adaptive Total Variation and Nonconvex Smoothly Clipped Absolute Deviation Penalty for Denoising Blocky Images	The total variation-based image denoising model has been generalized and extended in numerous ways, improving its performance in different contexts. We propose a new penalty function motivated by the recent progress in the statistical literature on high-dimensional variable selection. Using a particular instantiation o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	3,812
2106.06684	Multistream ValidNet: Improving 6D Object Pose Estimation by Automatic Multistream Validation	This work presents a novel approach to improve the results of pose estimation by detecting and distinguishing between the occurrence of True and False Positive results. It achieves this by training a binary classifier on the output of an arbitrary pose estimation algorithm, and returns a binary label indicating the val...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	240,576
2409.05712	Cooperative Decision-Making for CAVs at Unsignalized Intersections: A MARL Approach with Attention and Hierarchical Game Priors	The development of autonomous vehicles has shown great potential to enhance the efficiency and safety of transportation systems. However, the decision-making issue in complex human-machine mixed traffic scenarios, such as unsignalized intersections, remains a challenge for autonomous vehicles. While reinforcement learn...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	486,871
1905.12781	Learning to Crawl	Web crawling is the problem of keeping a cache of webpages fresh, i.e., having the most recent copy available when a page is requested. This problem is usually coupled with the natural restriction that the bandwidth available to the web crawler is limited. The corresponding optimization problem was solved optimally by ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,873
2412.01941	Global Average Feature Augmentation for Robust Semantic Segmentation with Transformers	Robustness to out-of-distribution data is crucial for deploying modern neural networks. Recently, Vision Transformers, such as SegFormer for semantic segmentation, have shown impressive robustness to visual corruptions like blur or noise affecting the acquisition device. In this paper, we propose Channel Wise Feature A...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,315
2212.06630	Differentially Private Tree-Based Redescription Mining	Differential privacy provides a strong form of privacy and allows preserving most of the original characteristics of the dataset. Utilizing these benefits requires one to design specific differentially private data analysis algorithms. In this work, we present three tree-based algorithms for mining redescriptions while...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	336,171
2409.04507	3D Data Long-Term Preservation in Cultural Heritage	The report explores the challenges and strategies for preserving 3D digital data in cultural heritage. It discusses the issue of technological obsolescence, emphasising the need for ustainable storage solutions and ongoing data management strategies. Key topics include understanding technological obsolescence, the life...	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	true	486,416
2211.13572	Physics-Based Object 6D-Pose Estimation during Non-Prehensile Manipulation	We propose a method to track the 6D pose of an object over time, while the object is under non-prehensile manipulation by a robot. At any given time during the manipulation of the object, we assume access to the robot joint controls and an image from a camera. We use the robot joint controls to perform a physics-based ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	332,521
2301.13192	Robust empirical risk minimization via Newton's method	A new variant of Newton's method for empirical risk minimization is studied, where at each iteration of the optimization algorithm, the gradient and Hessian of the objective function are replaced by robust estimators taken from existing literature on robust mean estimation for multivariate data. After proving a general...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	342,815
2307.00306	SyMFM6D: Symmetry-aware Multi-directional Fusion for Multi-View 6D Object Pose Estimation	Detecting objects and estimating their 6D poses is essential for automated systems to interact safely with the environment. Most 6D pose estimators, however, rely on a single camera frame and suffer from occlusions and ambiguities due to object symmetries. We overcome this issue by presenting a novel symmetry-aware mul...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	376,956
2110.05850	Improving Binary Neural Networks through Fully Utilizing Latent Weights	Binary Neural Networks (BNNs) rely on a real-valued auxiliary variable W to help binary training. However, pioneering binary works only use W to accumulate gradient updates during backward propagation, which can not fully exploit its power and may hinder novel advances in BNNs. In this work, we explore the role of W in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	260,427
1202.3750	Fractional Moments on Bandit Problems	Reinforcement learning addresses the dilemma between exploration to find profitable actions and exploitation to act according to the best observations already made. Bandit problems are one such class of problems in stateless environments that represent this explore/exploit situation. We propose a learning algorithm for...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	14,422
1610.00029	Microscopic Pedestrian Flow Characteristics: Development of an Image Processing Data Collection and Simulation Model	Microscopic pedestrian studies consider detailed interaction of pedestrians to control their movement in pedestrian traffic flow. The tools to collect the microscopic data and to analyze microscopic pedestrian flow are still very much in its infancy. The microscopic pedestrian flow characteristics need to be understood...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	61,780
2012.07237	Accurate Cell Segmentation in Digital Pathology Images via Attention Enforced Networks	Automatic cell segmentation is an essential step in the pipeline of computer-aided diagnosis (CAD), such as the detection and grading of breast cancer. Accurate segmentation of cells can not only assist the pathologists to make a more precise diagnosis, but also save much time and labor. However, this task suffers from...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	211,388
1804.07875	Multi-lingual Common Semantic Space Construction via Cluster-consistent Word Embedding	We construct a multilingual common semantic space based on distributional semantics, where words from multiple languages are projected into a shared space to enable knowledge and resource transfer across languages. Beyond word alignment, we introduce multiple cluster-level alignments and enforce the word clusters to be...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	95,624
1305.0321	Hidden Markov Model Identifiability via Tensors	The prevalence of hidden Markov models (HMMs) in various applications of statistical signal processing and communications is a testament to the power and flexibility of the model. In this paper, we link the identifiability problem with tensor decomposition, in particular, the Canonical Polyadic decomposition. Using rec...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	24,340
1806.09783	Understanding Dropout as an Optimization Trick	As one of standard approaches to train deep neural networks, dropout has been applied to regularize large models to avoid overfitting, and the improvement in performance by dropout has been explained as avoiding co-adaptation between nodes. However, when correlations between nodes are compared after training the networ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	101,419
2404.17288	ExcluIR: Exclusionary Neural Information Retrieval	Exclusion is an important and universal linguistic skill that humans use to express what they do not want. However, in information retrieval community, there is little research on exclusionary retrieval, where users express what they do not want in their queries. In this work, we investigate the scenario of exclusionar...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	449,809
2003.08376	Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting	Many autonomous systems forecast aspects of the future in order to aid decision-making. For example, self-driving vehicles and robotic manipulation systems often forecast future object poses by first detecting and tracking objects. However, this detect-then-forecast pipeline is expensive to scale, as pose forecasting a...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	true	false	false	false	168,719
1905.04232	Automatic Programming of Cellular Automata and Artificial Neural Networks Guided by Philosophy	Many computer models such as cellular automata and artificial neural networks have been developed and successfully applied. However, in some cases, these models might be restrictive on the possible solutions or their solutions might be difficult to interpret. To overcome this problem, we outline a new approach, the so-...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	true	false	true	130,409
2404.18327	MultiMAE-DER: Multimodal Masked Autoencoder for Dynamic Emotion Recognition	This paper presents a novel approach to processing multimodal data for dynamic emotion recognition, named as the Multimodal Masked Autoencoder for Dynamic Emotion Recognition (MultiMAE-DER). The MultiMAE-DER leverages the closely correlated representation information within spatiotemporal sequences across visual and au...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	450,221
1805.09639	Online Regularized Nonlinear Acceleration	Regularized nonlinear acceleration (RNA) estimates the minimum of a function by post-processing iterates from an algorithm such as the gradient method. It can be seen as a regularized version of Anderson acceleration, a classical acceleration scheme from numerical analysis. The new scheme provably improves the rate of ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	98,464
2312.01045	PROFL: A Privacy-Preserving Federated Learning Method with Stringent Defense Against Poisoning Attacks	Federated Learning (FL) faces two major issues: privacy leakage and poisoning attacks, which may seriously undermine the reliability and security of the system. Overcoming them simultaneously poses a great challenge. This is because privacy protection policies prohibit access to users' local gradients to avoid privacy ...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	412,284
2110.05803	SDWNet: A Straight Dilated Network with Wavelet Transformation for Image Deblurring	Image deblurring is a classical computer vision problem that aims to recover a sharp image from a blurred image. To solve this problem, existing methods apply the Encode-Decode architecture to design the complex networks to make a good performance. However, most of these methods use repeated up-sampling and down-sampli...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	260,409
1509.02768	Joint Relay and Jammer Selection Improves the Physical Layer Security in the Face of CSI Feedback Delays	We enhance the physical-layer security (PLS) of amplify-and-forward relaying networks with the aid of joint relay and jammer selection (JRJS), despite the deliterious effect of channel state information (CSI) feedback delays. Furthermore, we conceive a new outage-based characterization approach for the JRJS scheme. The...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	46,766
1909.09149	Timage -- A Robust Time Series Classification Pipeline	Time series are series of values ordered by time. This kind of data can be found in many real world settings. Classifying time series is a difficult task and an active area of research. This paper investigates the use of transfer learning in Deep Neural Networks and a 2D representation of time series known as Recurrenc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	146,168
2208.09910	Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation	In this work, we revisit the weak-to-strong consistency framework, popularized by FixMatch from semi-supervised classification, where the prediction of a weakly perturbed image serves as supervision for its strongly perturbed version. Intriguingly, we observe that such a simple pipeline already achieves competitive res...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	313,882
0809.3731	Uncertainty Relations for Shift-Invariant Analog Signals	The past several years have witnessed a surge of research investigating various aspects of sparse representations and compressed sensing. Most of this work has focused on the finite-dimensional setting in which the goal is to decompose a finite-length vector into a given finite dictionary. Underlying many of these resu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,395
1403.1177	Effects of temporal correlations on cascades: Threshold models on temporal networks	A person's decision to adopt an idea or product is often driven by the decisions of peers, mediated through a network of social ties. A common way of modeling adoption dynamics is to use threshold models, where a node may become an adopter given a high enough rate of contacts with adopted neighbors. We study the dynami...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	31,362
1811.06773	A Novel Approach to Sparse Inverse Covariance Estimation Using Transform Domain Updates and Exponentially Adaptive Thresholding	Sparse Inverse Covariance Estimation (SICE) is useful in many practical data analyses. Recovering the connectivity, non-connectivity graph of covariates is classified amongst the most important data mining and learning problems. In this paper, we introduce a novel SICE approach using adaptive thresholding. Our method i...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	113,597
2011.06983	A Secure Distributed Ledger for Transactive Energy: The Electron Volt Exchange (EVE) Blockchain	The adoption of blockchain for Transactive Energy has gained significant momentum as it allows mutually non-trusting agents to trade energy services in a trustless energy market. Research to date has assumed that the built-in Byzantine Fault Tolerance in recording transactions in a ledger is sufficient to ensure integr...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	206,403
1501.01811	Is "Compressed Sensing" compressive? Can it beat the Nyquist Sampling Approach?	Data compression capability of "Compressed sensing (sampling)" in signal discretization is numerically evaluated and found to be far from the theoretical upper bound defined by signal sparsity. It is shown that, for the cases when ordinary sampling with subsequent data compression is prohibitive, there is at least one ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,125
2410.23356	Sequential Order-Robust Mamba for Time Series Forecasting	Mamba has recently emerged as a promising alternative to Transformers, offering near-linear complexity in processing sequential data. However, while channels in time series (TS) data have no specific order in general, recent studies have adopted Mamba to capture channel dependencies (CD) in TS, introducing a sequential...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	504,011

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