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
1007.0465	On the Solvability of 2-pair Unicast Networks --- A Cut-based Characterization	In this paper, we propose a subnetwork decomposition/combination approach to investigate the single rate $2$-pair unicast problem. It is shown that the solvability of a $2$-pair unicast problem is completely determined by four specific link subsets, namely, $\mathcal A_{1,1}$, $\mathcal A_{2,2}$, $\mathcal A_{1,2}$ and...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	6,962
2303.07618	Medical Phrase Grounding with Region-Phrase Context Contrastive Alignment	Medical phrase grounding (MPG) aims to locate the most relevant region in a medical image, given a phrase query describing certain medical findings, which is an important task for medical image analysis and radiological diagnosis. However, existing visual grounding methods rely on general visual features for identifyin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,322
2407.18649	A survey of open-source data quality tools: shedding light on the materialization of data quality dimensions in practice	Data Quality (DQ) describes the degree to which data characteristics meet requirements and are fit for use by humans and/or systems. There are several aspects in which DQ can be measured, called DQ dimensions (i.e. accuracy, completeness, consistency, etc.), also referred to as characteristics in literature. ISO/IEC 25...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	476,469
1805.07429	Designing communication systems via iterative improvement: error correction coding with Bayes decoder and codebook optimized for source symbol error	In most error correction coding (ECC) frameworks, the typical error metric is the bit error rate (BER) which measures the number of bit errors. For this metric, the positions of the bits are not relevant to the decoding, and in many noise models, not relevant to the BER either. In many applications this is unsatisfacto...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	97,810
2310.18554	Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion	Logistic bandit is a ubiquitous framework of modeling users' choices, e.g., click vs. no click for advertisement recommender system. We observe that the prior works overlook or neglect dependencies in $S \geq \lVert \theta_\star \rVert_2$, where $\theta_\star \in \mathbb{R}^d$ is the unknown parameter vector, which is ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	403,593
2310.15417	A Semantic-driven Approach for Maintenance Digitalization in the Pharmaceutical Industry	The digital transformation of pharmaceutical industry is a challenging task due to the high complexity of involved elements and the strict regulatory compliance. Maintenance activities in the pharmaceutical industry play an essential role in ensuring product quality and integral functioning of equipment and premises. T...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	402,293
1912.07224	Domain Knowledge Based Brain Tumor Segmentation and Overall Survival Prediction	Automatically segmenting sub-regions of gliomas (necrosis, edema and enhancing tumor) and accurately predicting overall survival (OS) time from multimodal MRI sequences have important clinical significance in diagnosis, prognosis and treatment of gliomas. However, due to the high degree variations of heterogeneous appe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	157,551
2002.10936	Stochastic encoding of graphs in deep learning allows for complex analysis of gender classification in resting-state and task functional brain networks from the UK Biobank	Classification of whole-brain functional connectivity MRI data with convolutional neural networks (CNNs) has shown promise, but the complexity of these models impedes understanding of which aspects of brain activity contribute to classification. While visualization techniques have been developed to interpret CNNs, bias...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	165,554
cs/9901001	TDLeaf(lambda): Combining Temporal Difference Learning with Game-Tree Search	In this paper we present TDLeaf(lambda), a variation on the TD(lambda) algorithm that enables it to be used in conjunction with minimax search. We present some experiments in both chess and backgammon which demonstrate its utility and provide comparisons with TD(lambda) and another less radical variant, TD-directed(lam...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	540,459
1807.01750	Understanding and Accelerating Particle-Based Variational Inference	Particle-based variational inference methods (ParVIs) have gained attention in the Bayesian inference literature, for their capacity to yield flexible and accurate approximations. We explore ParVIs from the perspective of Wasserstein gradient flows, and make both theoretical and practical contributions. We unify variou...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	102,124
2401.10124	Lower Ricci Curvature for Efficient Community Detection	This study introduces the Lower Ricci Curvature (LRC), a novel, scalable, and scale-free discrete curvature designed to enhance community detection in networks. Addressing the computational challenges posed by existing curvature-based methods, LRC offers a streamlined approach with linear computational complexity, maki...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	422,495
2312.17106	Geometry-Biased Transformer for Robust Multi-View 3D Human Pose Reconstruction	We address the challenges in estimating 3D human poses from multiple views under occlusion and with limited overlapping views. We approach multi-view, single-person 3D human pose reconstruction as a regression problem and propose a novel encoder-decoder Transformer architecture to estimate 3D poses from multi-view 2D p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	418,619
2204.07692	FedVQCS: Federated Learning via Vector Quantized Compressed Sensing	In this paper, a new communication-efficient federated learning (FL) framework is proposed, inspired by vector quantized compressed sensing. The basic strategy of the proposed framework is to compress the local model update at each device by applying dimensionality reduction followed by vector quantization. Subsequentl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	291,801
1705.00835	Investigation of Different Skeleton Features for CNN-based 3D Action Recognition	Deep learning techniques are being used in skeleton based action recognition tasks and outstanding performance has been reported. Compared with RNN based methods which tend to overemphasize temporal information, CNN-based approaches can jointly capture spatio-temporal information from texture color images encoded from ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	72,760
1207.2641	Camera identification by grouping images from database, based on shared noise patterns	Previous research showed that camera specific noise patterns, so-called PRNU-patterns, are extracted from images and related images could be found. In this particular research the focus is on grouping images from a database, based on a shared noise pattern as an identification method for cameras. Using the method as de...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	17,408
1507.04761	Deep Learning and Music Adversaries	An adversary is essentially an algorithm intent on making a classification system perform in some particular way given an input, e.g., increase the probability of a false negative. Recent work builds adversaries for deep learning systems applied to image object recognition, which exploits the parameters of the system t...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	45,211
1903.08708	Accelerating Gradient Boosting Machine	Gradient Boosting Machine (GBM) is an extremely powerful supervised learning algorithm that is widely used in practice. GBM routinely features as a leading algorithm in machine learning competitions such as Kaggle and the KDDCup. In this work, we propose Accelerated Gradient Boosting Machine (AGBM) by incorporating Nes...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	124,886
2301.06268	Analyze the Effects of COVID-19 on Energy Storage Systems: A Techno-Economic Approach	During the COVID-19 pandemic, the U.S. power sector witnessed remarkable electricity demand changes in many geographical regions. these changes were evident in population-dense cities. This paper incorporates a techno-economic analysis of energy storage systems to investigate the pandemic's influence on ESS development...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	340,602
2407.08974	Topology-enhanced machine learning model (Top-ML) for anticancer peptide prediction	Recently, therapeutic peptides have demonstrated great promise for cancer treatment. To explore powerful anticancer peptides, artificial intelligence (AI)-based approaches have been developed to systematically screen potential candidates. However, the lack of efficient featurization of peptides has become a bottleneck ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	472,391
1906.08222	Deep Fuzzy Systems	An investigation of deep fuzzy systems is presented in this paper. A deep fuzzy system is represented by recursive fuzzy systems from an input terminal to output terminal. Recursive fuzzy systems are sequences of fuzzy grade memberships obtained using fuzzy transmition functions and recursive calls to fuzzy systems. A ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	135,806
2406.06397	Contrastive learning of T cell receptor representations	Computational prediction of the interaction of T cell receptors (TCRs) and their ligands is a grand challenge in immunology. Despite advances in high-throughput assays, specificity-labelled TCR data remains sparse. In other domains, the pre-training of language models on unlabelled data has been successfully used to ad...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	462,553
2210.07132	Learning Multivariate CDFs and Copulas using Tensor Factorization	Learning the multivariate distribution of data is a core challenge in statistics and machine learning. Traditional methods aim for the probability density function (PDF) and are limited by the curse of dimensionality. Modern neural methods are mostly based on black-box models, lacking identifiability guarantees. In thi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	323,585
2003.07577	Efficient Bitwidth Search for Practical Mixed Precision Neural Network	Network quantization has rapidly become one of the most widely used methods to compress and accelerate deep neural networks. Recent efforts propose to quantize weights and activations from different layers with different precision to improve the overall performance. However, it is challenging to find the optimal bitwid...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	168,477
2409.00303	Rapid and Robust Trajectory Optimization for Humanoids	Performing trajectory design for humanoid robots with high degrees of freedom is computationally challenging. The trajectory design process also often involves carefully selecting various hyperparameters and requires a good initial guess which can further complicate the development process. This work introduces a gener...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	484,867
1910.11299	Quick survey of graph-based fraud detection methods	In general, anomaly detection is the problem of distinguishing between normal data samples with well defined patterns or signatures and those that do not conform to the expected profiles. Financial transactions, customer reviews, social media posts are all characterized by relational information. In these networks, fra...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	150,738
1909.08787	On Efficient Multilevel Clustering via Wasserstein Distances	We propose a novel approach to the problem of multilevel clustering, which aims to simultaneously partition data in each group and discover grouping patterns among groups in a potentially large hierarchically structured corpus of data. Our method involves a joint optimization formulation over several spaces of discrete...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	146,057
1603.04871	Combining the Best of Convolutional Layers and Recurrent Layers: A Hybrid Network for Semantic Segmentation	State-of-the-art results of semantic segmentation are established by Fully Convolutional neural Networks (FCNs). FCNs rely on cascaded convolutional and pooling layers to gradually enlarge the receptive fields of neurons, resulting in an indirect way of modeling the distant contextual dependence. In this work, we advoc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	53,295
2107.07116	Transformer-based Machine Learning for Fast SAT Solvers and Logic Synthesis	CNF-based SAT and MaxSAT solvers are central to logic synthesis and verification systems. The increasing popularity of these constraint problems in electronic design automation encourages studies on different SAT problems and their properties for further computational efficiency. There has been both theoretical and pra...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	246,320
1803.04663	Binary Matrix Completion Using Unobserved Entries	A matrix completion problem, which aims to recover a complete matrix from its partial observations, is one of the important problems in the machine learning field and has been studied actively. However, there is a discrepancy between the mainstream problem setting, which assumes continuous-valued observations, and some...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	92,494
2403.05893	Estimating the Weight Enumerators of Reed-Muller Codes via Sampling	This paper develops an algorithmic approach for obtaining estimates of the weight enumerators of Reed-Muller (RM) codes. Our algorithm is based on a technique for estimating the partition functions of spin systems, which in turn employs a sampler that produces codewords according to a suitably defined Gibbs distributio...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	436,207
2012.08689	Domain Adaptive Object Detection via Feature Separation and Alignment	Recently, adversarial-based domain adaptive object detection (DAOD) methods have been developed rapidly. However, there are two issues that need to be resolved urgently. Firstly, numerous methods reduce the distributional shifts only by aligning all the feature between the source and target domain, while ignoring the p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	211,835
2410.07876	FDDM: Frequency-Decomposed Diffusion Model for Rectum Cancer Dose Prediction in Radiotherapy	Accurate dose distribution prediction is crucial in the radiotherapy planning. Although previous methods based on convolutional neural network have shown promising performance, they have the problem of over-smoothing, leading to prediction without important high-frequency details. Recently, diffusion model has achieved...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	496,842
1602.04506	Embracing Error to Enable Rapid Crowdsourcing	Microtask crowdsourcing has enabled dataset advances in social science and machine learning, but existing crowdsourcing schemes are too expensive to scale up with the expanding volume of data. To scale and widen the applicability of crowdsourcing, we present a technique that produces extremely rapid judgments for binar...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	52,151
2408.00167	Finch: Prompt-guided Key-Value Cache Compression	Recent large language model applications, such as Retrieval-Augmented Generation and chatbots, have led to an increased need to process longer input contexts. However, this requirement is hampered by inherent limitations. Architecturally, models are constrained by a context window defined during training. Additionally,...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	477,729
1507.01443	Nonparametric Bayesian Modeling for Automated Database Schema Matching	The problem of merging databases arises in many government and commercial applications. Schema matching, a common first step, identifies equivalent fields between databases. We introduce a schema matching framework that builds nonparametric Bayesian models for each field and compares them by computing the probability t...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	44,869
1707.01551	Improved User-Private Information Retrieval via Finite Geometry	In a User-Private Information Retrieval (UPIR) scheme, a set of users collaborate to retrieve files from a database without revealing to observers which participant in the scheme requested the file. Protocols have been proposed based on pairwise balanced designs and symmetric designs. Wepropose a new class of UPIR sche...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	76,560
2202.12801	On the data requirements of probing	As large and powerful neural language models are developed, researchers have been increasingly interested in developing diagnostic tools to probe them. There are many papers with conclusions of the form "observation X is found in model Y", using their own datasets with varying sizes. Larger probing datasets bring more ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	282,364
2309.10966	MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods	Recent research in decoding methods for Natural Language Generation (NLG) tasks has shown that MAP decoding is not optimal, because model probabilities do not always align with human preferences. Stronger decoding methods, including Quality Estimation (QE) reranking and Minimum Bayes' Risk (MBR) decoding, have since be...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	393,219
2301.13546	Joint Task Offloading and Cache Placement for Energy-Efficient Mobile Edge Computing Systems	This letter investigates a cache-enabled multiuser mobile edge computing (MEC) system with dynamic task arrivals, taking into account the impact of proactive cache placement on the system's overall energy consumption. We consider that an access point (AP) schedules a wireless device (WD) to offload computational tasks ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	342,954
2207.02845	Automating the Design and Development of Gradient Descent Trained Expert System Networks	Prior work introduced a gradient descent trained expert system that conceptually combines the learning capabilities of neural networks with the understandability and defensible logic of an expert system. This system was shown to be able to learn patterns from data and to perform decision-making at levels rivaling those...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	306,637
1904.13383	Comparative evaluation of 2D feature correspondence selection algorithms	Correspondence selection aiming at seeking correct feature correspondences from raw feature matches is pivotal for a number of feature-matching-based tasks. Various 2D (image) correspondence selection algorithms have been presented with decades of progress. Unfortunately, the lack of an in-depth evaluation makes it dif...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	129,374
2009.14589	Hidden Markov Models for Pipeline Damage Detection Using Piezoelectric Transducers	Oil and gas pipeline leakages lead to not only enormous economic loss but also environmental disasters. How to detect the pipeline damages including leakages and cracks has attracted much research attention. One of the promising leakage detection method is to use lead zirconate titanate (PZT) transducers to detect the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	198,083
2102.10094	Formal Language Theory Meets Modern NLP	NLP is deeply intertwined with the formal study of language, both conceptually and historically. Arguably, this connection goes all the way back to Chomsky's Syntactic Structures in 1957. It also still holds true today, with a strand of recent works building formal analysis of modern neural networks methods in terms of...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	220,975
2407.20383	Appraisal-Guided Proximal Policy Optimization: Modeling Psychological Disorders in Dynamic Grid World	The integration of artificial intelligence across multiple domains has emphasized the importance of replicating human-like cognitive processes in AI. By incorporating emotional intelligence into AI agents, their emotional stability can be evaluated to enhance their resilience and dependability in critical decision-maki...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	477,149
2004.10078	AMP-Net: Denoising based Deep Unfolding for Compressive Image Sensing	Most compressive sensing (CS) reconstruction methods can be divided into two categories, i.e. model-based methods and classical deep network methods. By unfolding the iterative optimization algorithm for model-based methods onto networks, deep unfolding methods have the good interpretation of model-based methods and th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	173,535
2410.18527	Probing Ranking LLMs: Mechanistic Interpretability in Information Retrieval	Transformer networks, especially those with performance on par with GPT models, are renowned for their powerful feature extraction capabilities. However, the nature and correlation of these features with human-engineered ones remain unclear. In this study, we delve into the mechanistic workings of state-of-the-art, fin...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	501,924
2404.03898	VoltaVision: A Transfer Learning model for electronic component classification	In this paper, we analyze the effectiveness of transfer learning on classifying electronic components. Transfer learning reuses pre-trained models to save time and resources in building a robust classifier rather than learning from scratch. Our work introduces a lightweight CNN, coined as VoltaVision, and compares its ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	444,443
2303.06908	CrossFormer++: A Versatile Vision Transformer Hinging on Cross-scale Attention	While features of different scales are perceptually important to visual inputs, existing vision transformers do not yet take advantage of them explicitly. To this end, we first propose a cross-scale vision transformer, CrossFormer. It introduces a cross-scale embedding layer (CEL) and a long-short distance attention (L...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,049
2502.09688	Towards Virtual Clinical Trials of Radiology AI with Conditional Generative Modeling	Artificial intelligence (AI) is poised to transform healthcare by enabling personalized and efficient care through data-driven insights. Although radiology is at the forefront of AI adoption, in practice, the potential of AI models is often overshadowed by severe failures to generalize: AI models can have performance d...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	533,564
cs/0703017	Performance Bounds for Bi-Directional Coded Cooperation Protocols	In coded bi-directional cooperation, two nodes wish to exchange messages over a shared half-duplex channel with the help of a relay. In this paper, we derive performance bounds for this problem for each of three protocols. The first protocol is a two phase protocol were both users simultaneously transmit during the f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,212
2401.07947	Delivery Line Tracking Robot	The project we embarked on is making an electronic robot that can deliver a package along a set route through infrared sensors. It uses the infrared sensors to determine if the path it is following is correct or if it is off course. This is determined by sending off a photon to reflect off the path and determines if it...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	421,706
2203.03719	Biometric recognition: why not massively adopted yet?	Although there has been a dramatically reduction on the prices of capturing devices and an increase on computing power in the last decade, it seems that biometric systems are still far from massive adoption for civilian applications. This paper deals with the causes of this phenomenon, as well as some misconceptions re...	false	false	false	false	false	false	true	false	false	false	false	true	true	true	false	false	false	false	284,196
2502.11330	System Message Generation for User Preferences using Open-Source Models	System messages play a crucial role in interactions with large language models (LLMs), often serving as prompts to initiate conversations. Through system messages, users can assign specific roles, perform intended tasks, incorporate background information, specify various output formats and communication styles. Despit...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	534,304
2209.09300	PoxVerifi: An Information Verification System to Combat Monkeypox Misinformation	Following recent outbreaks, monkeypox-related misinformation continues to rapidly spread online. This negatively impacts response strategies and disproportionately harms LGBTQ+ communities in the short-term, and ultimately undermines the overall effectiveness of public health responses. In an attempt to combat monkeypo...	false	false	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	318,452
2403.07853	Improving Fairness in Photovoltaic Curtailments via Daily Topology Reconfiguration for Voltage Control in Power Distribution Networks	In PV-rich power distribution systems, over-voltage issues are often addressed by curtailing excess generation from PV plants (in addition to reactive power control), raising fairness concerns. Existing fairness-aware control schemes tackle this problem by incorporating fairness objectives into the cost function. Howev...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	437,051
2206.08910	niksss at HinglishEval: Language-agnostic BERT-based Contextual Embeddings with Catboost for Quality Evaluation of the Low-Resource Synthetically Generated Code-Mixed Hinglish Text	This paper describes the system description for the HinglishEval challenge at INLG 2022. The goal of this task was to investigate the factors influencing the quality of the code-mixed text generation system. The task was divided into two subtasks, quality rating prediction and annotators disagreement prediction of the ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	303,349
2109.04698	Face-NMS: A Core-set Selection Approach for Efficient Face Recognition	Recently, face recognition in the wild has achieved remarkable success and one key engine is the increasing size of training data. For example, the largest face dataset, WebFace42M contains about 2 million identities and 42 million faces. However, a massive number of faces raise the constraints in training time, comput...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	254,500
1603.02041	Learning Shared Representations in Multi-task Reinforcement Learning	We investigate a paradigm in multi-task reinforcement learning (MT-RL) in which an agent is placed in an environment and needs to learn to perform a series of tasks, within this space. Since the environment does not change, there is potentially a lot of common ground amongst tasks and learning to solve them individuall...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	52,975
1608.04170	Every Filter Extracts A Specific Texture In Convolutional Neural Networks	Many works have concentrated on visualizing and understanding the inner mechanism of convolutional neural networks (CNNs) by generating images that activate some specific neurons, which is called deep visualization. However, it is still unclear what the filters extract from images intuitively. In this paper, we propose...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,788
1412.4205	The application of the Bayes Ying Yang harmony based GMMs in on-line signature verification	In this contribution, a Bayes Ying Yang(BYY) harmony based approach for on-line signature verification is presented. In the proposed method, a simple but effective Gaussian Mixture Models(GMMs) is used to represent for each user's signature model based on the prior information collected. Different from the early works,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	38,367
1910.05674	Structure-preserving Interpolatory Model Reduction for Port-Hamiltonian Differential-Algebraic Systems	We examine interpolatory model reduction methods that are well-suited for treating large scale port-Hamiltonian differential-algebraic systems in a way that is able to preserve and indeed, take advantage of the underlying structural features of the system. We introduce approaches that incorporate regularization togethe...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	149,139
2109.00621	Grassmannian Constellation Design for Noncoherent MIMO Systems Using Autoencoders	In this letter, we propose an autoencoder (AE) for designing Grassmannian constellations in noncoherent (NC) multiple-input multiple-output (MIMO) systems. To guarantee the properties of Grassmannian constellations, the proposed AE constructs the transmitted symbols following an unitary space-time modulation. It penali...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	253,164
2502.02628	e-SimFT: Alignment of Generative Models with Simulation Feedback for Pareto-Front Design Exploration	Deep generative models have recently shown success in solving complex engineering design problems where models predict solutions that address the design requirements specified as input. However, there remains a challenge in aligning such models for effective design exploration. For many design problems, finding a solut...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	530,403
2205.05810	Performing Video Frame Prediction of Microbial Growth with a Recurrent Neural Network	A Recurrent Neural Network (RNN) was used to perform video frame prediction of microbial growth for a population of two mutants of Pseudomonas aeruginosa. The RNN was trained on videos of 20 frames that were acquired using fluorescence microscopy and microfluidics. The network predicted the last 10 frames of each video...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	296,044
1709.07092	On Compiling DNNFs without Determinism	State-of-the-art knowledge compilers generate deterministic subsets of DNNF, which have been recently shown to be exponentially less succinct than DNNF. In this paper, we propose a new method to compile DNNFs without enforcing determinism necessarily. Our approach is based on compiling deterministic DNNFs with the addi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	81,218
2201.00598	Toxicity Detection for Indic Multilingual Social Media Content	Toxic content is one of the most critical issues for social media platforms today. India alone had 518 million social media users in 2020. In order to provide a good experience to content creators and their audience, it is crucial to flag toxic comments and the users who post that. But the big challenge is identifying ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	274,009
2108.05680	Lutz's Spoiler Technique Revisited: A Unified Approach to Worst-Case Optimal Entailment of Unions of Conjunctive Queries in Locally-Forward Description Logics	We present a unified approach to (both finite and unrestricted) worst-case optimal entailment of (unions of) conjunctive queries (U)CQs in the wide class of "locally-forward" description logics. The main technique that we employ is a generalisation of Lutz's spoiler technique, originally developed for CQ entailment in ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	250,379
2408.15554	A Novel Denoising Technique and Deep Learning Based Hybrid Wind Speed Forecasting Model for Variable Terrain Conditions	Wind flow can be highly unpredictable and can suffer substantial fluctuations in speed and direction due to the shape and height of hills, mountains, and valleys, making accurate wind speed (WS) forecasting essential in complex terrain. This paper presents a novel and adaptive model for short-term forecasting of WS. Th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	483,979
2212.08816	Improving Unsupervised Video Object Segmentation with Motion-Appearance Synergy	We present IMAS, a method that segments the primary objects in videos without manual annotation in training or inference. Previous methods in unsupervised video object segmentation (UVOS) have demonstrated the effectiveness of motion as either input or supervision for segmentation. However, motion signals may be uninfo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	336,883
2002.00417	WaveTTS: Tacotron-based TTS with Joint Time-Frequency Domain Loss	Tacotron-based text-to-speech (TTS) systems directly synthesize speech from text input. Such frameworks typically consist of a feature prediction network that maps character sequences to frequency-domain acoustic features, followed by a waveform reconstruction algorithm or a neural vocoder that generates the time-domai...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	162,345
2212.07721	Deep Learning-Based Automatic Assessment of AgNOR-scores in Histopathology Images	Nucleolar organizer regions (NORs) are parts of the DNA that are involved in RNA transcription. Due to the silver affinity of associated proteins, argyrophilic NORs (AgNORs) can be visualized using silver-based staining. The average number of AgNORs per nucleus has been shown to be a prognostic factor for predicting th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	336,499
2208.09052	A Review of Uncertainty for Deep Reinforcement Learning	Uncertainty is ubiquitous in games, both in the agents playing games and often in the games themselves. Working with uncertainty is therefore an important component of successful deep reinforcement learning agents. While there has been substantial effort and progress in understanding and working with uncertainty for su...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	313,573
2205.10312	ClusterEA: Scalable Entity Alignment with Stochastic Training and Normalized Mini-batch Similarities	Entity alignment (EA) aims at finding equivalent entities in different knowledge graphs (KGs). Embedding-based approaches have dominated the EA task in recent years. Those methods face problems that come from the geometric properties of embedding vectors, including hubness and isolation. To solve these geometric proble...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	true	false	297,648
2002.10769	Can speed up the convergence rate of stochastic gradient methods to $\mathcal{O}(1/k^2)$ by a gradient averaging strategy?	In this paper we consider the question of whether it is possible to apply a gradient averaging strategy to improve on the sublinear convergence rates without any increase in storage. Our analysis reveals that a positive answer requires an appropriate averaging strategy and iterations that satisfy the variance dominant ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	165,510
2109.14478	Quadratic-Curve-Lifted Reed-Solomon Codes	Lifted codes are a class of evaluation codes attracting more attention due to good locality and intermediate availability. In this work we introduce and study quadratic-curve-lifted Reed-Solomon (QC-LRS) codes, where the codeword symbols whose coordinates are on a quadratic curve form a codeword of a Reed-Solomon code....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	257,976
1909.11359	Tackling Long-Tailed Relations and Uncommon Entities in Knowledge Graph Completion	For large-scale knowledge graphs (KGs), recent research has been focusing on the large proportion of infrequent relations which have been ignored by previous studies. For example few-shot learning paradigm for relations has been investigated. In this work, we further advocate that handling uncommon entities is inevitab...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	146,792
1911.02140	Fully Parameterized Quantile Function for Distributional Reinforcement Learning	Distributional Reinforcement Learning (RL) differs from traditional RL in that, rather than the expectation of total returns, it estimates distributions and has achieved state-of-the-art performance on Atari Games. The key challenge in practical distributional RL algorithms lies in how to parameterize estimated distrib...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	152,286
1808.10600	Content-based feature exploration for transparent music recommendation using self-attentive genre classification	Interpretation of retrieved results is an important issue in music recommender systems, particularly from a user perspective. In this study, we investigate the methods for providing interpretability of content features using self-attention. We extract lyric features with the self-attentive genre classification model tr...	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	106,413
2303.17650	Comparing Abstractive Summaries Generated by ChatGPT to Real Summaries Through Blinded Reviewers and Text Classification Algorithms	Large Language Models (LLMs) have gathered significant attention due to their impressive performance on a variety of tasks. ChatGPT, developed by OpenAI, is a recent addition to the family of language models and is being called a disruptive technology by a few, owing to its human-like text-generation capabilities. Alth...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	355,295
2111.00789	Learning Inertial Odometry for Dynamic Legged Robot State Estimation	This paper introduces a novel proprioceptive state estimator for legged robots based on a learned displacement measurement from IMU data. Recent research in pedestrian tracking has shown that motion can be inferred from inertial data using convolutional neural networks. A learned inertial displacement measurement can i...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	264,344
2407.04573	VRSD: Rethinking Similarity and Diversity for Retrieval in Large Language Models	Vector retrieval algorithms are essential for semantic queries within the rapidly evolving landscape of Large Language Models (LLMs). The ability to retrieve vectors that satisfy both similarity and diversity criteria substantially enhances the performance of LLMs. Although Maximal Marginal Relevance (MMR) is widely em...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	470,612
2109.08501	SaCoFa: Semantics-aware Control-flow Anonymization for Process Mining	Privacy-preserving process mining enables the analysis of business processes using event logs, while giving guarantees on the protection of sensitive information on process stakeholders. To this end, existing approaches add noise to the results of queries that extract properties of an event log, such as the frequency d...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	true	false	255,921
2408.13082	Multivariate Time-Series Anomaly Detection based on Enhancing Graph Attention Networks with Topological Analysis	Unsupervised anomaly detection in time series is essential in industrial applications, as it significantly reduces the need for manual intervention. Multivariate time series pose a complex challenge due to their feature and temporal dimensions. Traditional methods use Graph Neural Networks (GNNs) or Transformers to ana...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	483,001
2312.17579	Distribution-based Low-rank Embedding	The early detection of breast abnormalities is a matter of critical significance. Notably, infrared thermography has emerged as a valuable tool in breast cancer screening and clinical breast examination (CBE). Measuring heterogeneous thermal patterns is the key to incorporating computational dynamic thermography, which...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	418,797
2110.13057	Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models	Federated learning has quickly gained popularity with its promises of increased user privacy and efficiency. Previous works have shown that federated gradient updates contain information that can be used to approximately recover user data in some situations. These previous attacks on user privacy have been limited in s...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	263,056
1309.2505	Compressed Sensing for Block-Sparse Smooth Signals	We present reconstruction algorithms for smooth signals with block sparsity from their compressed measurements. We tackle the issue of varying group size via group-sparse least absolute shrinkage selection operator (LASSO) as well as via latent group LASSO regularizations. We achieve smoothness in the signal via fusion...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	26,954
2411.19635	Build An Influential Bot In Social Media Simulations With Large Language Models	Understanding the dynamics of public opinion evolution on online social platforms is critical for analyzing influence mechanisms. Traditional approaches to influencer analysis are typically divided into qualitative assessments of personal attributes and quantitative evaluations of influence power. In this study, we int...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	512,331
1105.0785	Coupled Graphical Models and Their Thresholds	The excellent performance of convolutional low-density parity-check codes is the result of the spatial coupling of individual underlying codes across a window of growing size, but much smaller than the length of the individual codes. Remarkably, the belief-propagation threshold of the coupled ensemble is boosted to the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	10,244
2410.23321	Beyond Current Boundaries: Integrating Deep Learning and AlphaFold for Enhanced Protein Structure Prediction from Low-Resolution Cryo-EM Maps	Constructing atomic models from cryo-electron microscopy (cryo-EM) maps is a crucial yet intricate task in structural biology. While advancements in deep learning, such as convolutional neural networks (CNNs) and graph neural networks (GNNs), have spurred the development of sophisticated map-to-model tools like DeepTra...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,000
2209.13023	Lex2Sent: A bagging approach to unsupervised sentiment analysis	Unsupervised text classification, with its most common form being sentiment analysis, used to be performed by counting words in a text that were stored in a lexicon, which assigns each word to one class or as a neutral word. In recent years, these lexicon-based methods fell out of favor and were replaced by computation...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	319,743
2401.05236	Structure from Duplicates: Neural Inverse Graphics from a Pile of Objects	Our world is full of identical objects (\emphe.g., cans of coke, cars of same model). These duplicates, when seen together, provide additional and strong cues for us to effectively reason about 3D. Inspired by this observation, we introduce Structure from Duplicates (SfD), a novel inverse graphics framework that recons...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	420,692
1303.0783	Epidemic threshold in directed networks	Epidemics have so far been mostly studied in undirected networks. However, many real-world networks, such as the social network Twitter and the WWW networks, upon which information, emotion or malware spreads, are shown to be directed networks, composed of both unidirectional links and bidirectional links. We define th...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	22,620
2105.07346	Understanding the Effect of Bias in Deep Anomaly Detection	Anomaly detection presents a unique challenge in machine learning, due to the scarcity of labeled anomaly data. Recent work attempts to mitigate such problems by augmenting training of deep anomaly detection models with additional labeled anomaly samples. However, the labeled data often does not align with the target d...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	235,401
2103.13813	RA-BNN: Constructing Robust & Accurate Binary Neural Network to Simultaneously Defend Adversarial Bit-Flip Attack and Improve Accuracy	Recently developed adversarial weight attack, a.k.a. bit-flip attack (BFA), has shown enormous success in compromising Deep Neural Network (DNN) performance with an extremely small amount of model parameter perturbation. To defend against this threat, we propose RA-BNN that adopts a complete binary (i.e., for both weig...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	226,618
1205.1225	Volumetric Mapping of Genus Zero Objects via Mass Preservation	In this work, we present a technique to map any genus zero solid object onto a hexahedral decomposition of a solid cube. This problem appears in many applications ranging from finite element methods to visual tracking. From this, one can then hopefully utilize the proposed technique for shape analysis, registration, as...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	15,814
2401.12851	Classification of grapevine varieties using UAV hyperspectral imaging	The classification of different grapevine varieties is a relevant phenotyping task in Precision Viticulture since it enables estimating the growth of vineyard rows dedicated to different varieties, among other applications concerning the wine industry. This task can be performed with destructive methods that require ti...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	423,517
2306.17439	Provable Robust Watermarking for AI-Generated Text	We study the problem of watermarking large language models (LLMs) generated text -- one of the most promising approaches for addressing the safety challenges of LLM usage. In this paper, we propose a rigorous theoretical framework to quantify the effectiveness and robustness of LLM watermarks. We propose a robust and h...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	376,700
1911.12618	Machine learning for music genre: multifaceted review and experimentation with audioset	Music genre classification is one of the sub-disciplines of music information retrieval (MIR) with growing popularity among researchers, mainly due to the already open challenges. Although research has been prolific in terms of number of published works, the topic still suffers from a problem in its foundations: there ...	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	155,455
2303.17560	Closing the gap between research and projects in climate change innovation in Europe	Innovation is a key component to equip our society with tools to adapt to new climatic conditions. The development of research-action interfaces shifts useful ideas into operationalized knowledge allowing innovation to flourish. In this paper we quantify the existing gap between climate research and innovation action i...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	355,248
1901.06905	Equality in the Matrix Entropy-Power Inequality and Blind Separation of Real and Complex sources	The matrix version of the entropy-power inequality for real or complex coefficients and variables is proved using a transportation argument that easily settles the equality case. An application to blind source extraction is given.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	119,113

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