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
1704.08531	A Survey of Neural Network Techniques for Feature Extraction from Text	This paper aims to catalyze the discussions about text feature extraction techniques using neural network architectures. The research questions discussed in the paper focus on the state-of-the-art neural network techniques that have proven to be useful tools for language processing, language generation, text classifica...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	72,534
0906.1593	On Defining 'I' "I logy"	Could we define I? Throughout this article we give a negative answer to this question. More exactly, we show that there is no definition for I in a certain way. But this negative answer depends on our definition of definability. Here, we try to consider sufficient generalized definition of definability. In the middle o...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	3,847
2305.18247	TaleCrafter: Interactive Story Visualization with Multiple Characters	Accurate Story visualization requires several necessary elements, such as identity consistency across frames, the alignment between plain text and visual content, and a reasonable layout of objects in images. Most previous works endeavor to meet these requirements by fitting a text-to-image (T2I) model on a set of vide...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	368,917
2412.14978	Spectrum-based Modality Representation Fusion Graph Convolutional Network for Multimodal Recommendation	Incorporating multi-modal features as side information has recently become a trend in recommender systems. To elucidate user-item preferences, recent studies focus on fusing modalities via concatenation, element-wise sum, or attention mechanisms. Despite having notable success, existing approaches do not account for th...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	518,912
2310.20285	Accelerating Generalized Linear Models by Trading off Computation for Uncertainty	Bayesian Generalized Linear Models (GLMs) define a flexible probabilistic framework to model categorical, ordinal and continuous data, and are widely used in practice. However, exact inference in GLMs is prohibitively expensive for large datasets, thus requiring approximations in practice. The resulting approximation e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	404,331
2407.12000	The Kolmogorov Complexity of Irish traditional dance music	We estimate the Kolmogorov complexity of melodies in Irish traditional dance music using Lempel-Ziv compression. The "tunes" of the music are presented in so-called "ABC notation" as simply a sequence of letters from an alphabet: We have no rhythmic variation, with all notes being of equal length. Our estimation of alg...	false	false	true	false	false	true	false	false	true	true	false	true	false	false	false	false	false	false	473,712
1505.07672	A Generative Model of Natural Texture Surrogates	Natural images can be viewed as patchworks of different textures, where the local image statistics is roughly stationary within a small neighborhood but otherwise varies from region to region. In order to model this variability, we first applied the parametric texture algorithm of Portilla and Simoncelli to image patch...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	43,560
2501.12547	Human-like conceptual representations emerge from language prediction	Recent advances in large language models (LLMs) provide a new opportunity to address the long-standing question of how concepts are represented and organized in the mind, which is central to unravelling the nature of human cognition. Here, we reframed the classic reverse dictionary task to simulate human concept infere...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	526,353
2001.09130	Creating Realistic Power Distribution Networks using Interdependent Road Infrastructure	It is well known that physical interdependencies exist between networked civil infrastructures such as transportation and power system networks. In order to analyze complex nonlinear correlations between such networks, datasets pertaining to such real infrastructures are required. However, such data are not readily ava...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	161,485
1905.09440	One-bit LFMCW Radar: Spectrum Analysis and Target Detection	One-bit radar, performing signal sampling and quantization by a one-bit ADC, is a promising technology for many civilian applications due to its low-cost and low-power consumptions. In this paper, problems encountered by one-bit LFMCW radar are studied and a two-stage target detection method termed as the dimension-red...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	131,734
2109.11237	Pregroup Grammars, their Syntax and Semantics	Pregroup grammars were developed in 1999 and stayed Lambek's preferred algebraic model of grammar. The set-theoretic semantics of pregroups, however, faces an ambiguity problem. In his latest book, Lambek suggests that this problem might be overcome using finite dimensional vector spaces rather than sets. What is the r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	256,880
1903.00752	Interference Mitigation via Rate-Splitting and Common Message Decoding in Cloud Radio Access Networks	Cloud-radio access networks (C-RAN) help overcoming the scarcity of radio resources by enabling dense deployment of base-stations (BSs), and connecting them to a central-processor (CP). This paper considers the downlink of a C-RAN, where the cloud is connected to the BSs via limited-capacity backhaul links. The paper p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	123,092
2012.15161	Universal Urban Spreading Pattern of COVID-19 and Its Underlying Mechanism	Currently, the global situation of COVID-19 is aggravating, pressingly calling for efficient control and prevention measures. Understanding spreading pattern of COVID-19 has been widely recognized as a vital step for implementing non-pharmaceutical measures. Previous studies investigated such an issue in large-scale (e...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	213,711
2012.03197	DGGAN: Depth-image Guided Generative Adversarial Networks for Disentangling RGB and Depth Images in 3D Hand Pose Estimation	Estimating3D hand poses from RGB images is essentialto a wide range of potential applications, but is challengingowing to substantial ambiguity in the inference of depth in-formation from RGB images. State-of-the-art estimators ad-dress this problem by regularizing3D hand pose estimationmodels during training to enforc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	210,028
2407.10720	Semantic Units: Increasing Expressivity and Simplicity of Formal Representations of Data and Knowledge in Knowledge Graphs	Knowledge graphs and ontologies are becoming increasingly vital as they align with the FAIR Guiding Principles (Findable, Accessible, Interoperable, Reusable). We address eleven challenges that may impede the full realization of the potential of FAIR knowledge graphs, as conventional solutions are perceived to be overl...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	473,095
1801.00563	Block Diagonalization Type Precoding Algorithms for IEEE 802.11ac Systems	Block diagonalization (BD) based precoding schemes are well-known linear transmit strategies employed in the downlink of multi-user multiple-input multipleoutput (MU-MIMO) systems. BD type precoding algorithms employed at the transmit side effect the suppression of multi-user interference (MUI) by the decomposition of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	87,590
2401.13387	A Mathematical Theory of Semantic Communication	The year 1948 witnessed the historic moment of the birth of classic information theory (CIT). Guided by CIT, modern communication techniques have approached the theoretic limitations, such as, entropy function $H(U)$, channel capacity $C=\max_{p(x)}I(X;Y)$ and rate-distortion function $R(D)=\min_{p(\hat{x}\|x):\mathbb{E...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	423,710
2005.01777	ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents	We present ADVISER - an open-source, multi-domain dialog system toolkit that enables the development of multi-modal (incorporating speech, text and vision), socially-engaged (e.g. emotion recognition, engagement level prediction and backchanneling) conversational agents. The final Python-based implementation of our too...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	175,667
2208.07054	A novel computational technique using coefficient diagram method for load frequency control in an interconnected power system	This paper proposes a novel load frequency control (LFC) approach formulated on an optimal structure of the coefficient diagram method (CDM) in a two-area thermal power system. As part of a realistic analysis, nonlinearities related to governor dead band (GDB) and generation rate constraint (GRC) have been considered. ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	312,924
1412.6160	H infinity Analysis Revisited	This paper proposes a direct, and simple approach to the H infinity norm calculation in more general settings. In contrast to the method based on the Kalman-Yakubovich-Popov lemma, our approach does not require a controllability assumption, and returns a sinusoidal input that achieves the H infinity norm of the system ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	38,594
2206.03206	FlexLip: A Controllable Text-to-Lip System	The task of converting text input into video content is becoming an important topic for synthetic media generation. Several methods have been proposed with some of them reaching close-to-natural performances in constrained tasks. In this paper, we tackle a subissue of the text-to-video generation problem, by converting...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	301,180
2408.06541	Interactive Coding with Small Memory and Improved Rate	In this work, we study two-party interactive coding for adversarial noise, when both parties have limited memory. We show how to convert any adaptive protocol $\Pi$ into a protocol $\Pi'$ that is robust to an $\epsilon$-fraction of adversarial corruptions, not too much longer than $\Pi$, and which uses small space. Mor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	480,241
2304.00488	Saddle-to-Saddle Dynamics in Diagonal Linear Networks	In this paper we fully describe the trajectory of gradient flow over diagonal linear networks in the limit of vanishing initialisation. We show that the limiting flow successively jumps from a saddle of the training loss to another until reaching the minimum $\ell_1$-norm solution. This saddle-to-saddle dynamics transl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	355,709
2011.02761	Instance Based Approximations to Profile Maximum Likelihood	In this paper we provide a new efficient algorithm for approximately computing the profile maximum likelihood (PML) distribution, a prominent quantity in symmetric property estimation. We provide an algorithm which matches the previous best known efficient algorithms for computing approximate PML distributions and impr...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	205,026
1609.02781	An empirical study on the effects of different types of noise in image classification tasks	Image classification is one of the main research problems in computer vision and machine learning. Since in most real-world image classification applications there is no control over how the images are captured, it is necessary to consider the possibility that these images might be affected by noise (e.g. sensor noise ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	60,781
2411.16064	Multi-Granularity Class Prototype Topology Distillation for Class-Incremental Source-Free Unsupervised Domain Adaptation	This paper explores the Class-Incremental Source-Free Unsupervised Domain Adaptation (CI-SFUDA) problem, where the unlabeled target data come incrementally without access to labeled source instances. This problem poses two challenges, the disturbances of similar source-class knowledge to target-class representation lea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	510,872
2212.03244	Synthetic Expertise	We will soon be surrounded by artificial systems capable of cognitive performance rivaling or exceeding a human expert in specific domains of discourse. However, these cogs need not be capable of full general artificial intelligence nor able to function in a stand-alone manner. Instead, cogs and humans will work togeth...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	335,047
2310.09893	Adaptive Contact-Implicit Model Predictive Control with Online Residual Learning	The hybrid nature of multi-contact robotic systems, due to making and breaking contact with the environment, creates significant challenges for high-quality control. Existing model-based methods typically rely on either good prior knowledge of the multi-contact model or require significant offline model tuning effort, ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	399,997
0911.0467	On Secure Network Coding with Nonuniform or Restricted Wiretap Sets	The secrecy capacity of a network, for a given collection of permissible wiretap sets, is the maximum rate of communication such that observing links in any permissible wiretap set reveals no information about the message. This paper considers secure network coding with nonuniform or restricted wiretap sets, for exampl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,845
1911.10708	hauWE: Hausa Words Embedding for Natural Language Processing	Words embedding (distributed word vector representations) have become an essential component of many natural language processing (NLP) tasks such as machine translation, sentiment analysis, word analogy, named entity recognition and word similarity. Despite this, the only work that provides word vectors for Hausa langu...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	154,916
2202.04208	Validating Causal Inference Methods	The fundamental challenge of drawing causal inference is that counterfactual outcomes are not fully observed for any unit. Furthermore, in observational studies, treatment assignment is likely to be confounded. Many statistical methods have emerged for causal inference under unconfoundedness conditions given pre-treatm...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,487
2210.10749	Transformers Learn Shortcuts to Automata	Algorithmic reasoning requires capabilities which are most naturally understood through recurrent models of computation, like the Turing machine. However, Transformer models, while lacking recurrence, are able to perform such reasoning using far fewer layers than the number of reasoning steps. This raises the question:...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	325,046
2304.00601	Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies	Transformations based on domain expertise (expert transformations), such as random-resized-crop and color-jitter, have proven critical to the success of contrastive learning techniques such as SimCLR. Recently, several attempts have been made to replace such domain-specific, human-designed transformations with generate...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	355,749
1910.06151	Sampling-based sublinear low-rank matrix arithmetic framework for dequantizing quantum machine learning	We present an algorithmic framework for quantum-inspired classical algorithms on close-to-low-rank matrices, generalizing the series of results started by Tang's breakthrough quantum-inspired algorithm for recommendation systems [STOC'19]. Motivated by quantum linear algebra algorithms and the quantum singular value tr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	149,274
1712.00311	Folded Recurrent Neural Networks for Future Video Prediction	Future video prediction is an ill-posed Computer Vision problem that recently received much attention. Its main challenges are the high variability in video content, the propagation of errors through time, and the non-specificity of the future frames: given a sequence of past frames there is a continuous distribution o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,876
2008.05556	Model-Based Offline Planning	Offline learning is a key part of making reinforcement learning (RL) useable in real systems. Offline RL looks at scenarios where there is data from a system's operation, but no direct access to the system when learning a policy. Recent work on training RL policies from offline data has shown results both with model-fr...	false	false	false	false	true	false	true	true	false	false	true	false	false	false	false	false	false	false	191,534
1905.02940	A new direction to promote the implementation of artificial intelligence in natural clinical settings	Artificial intelligence (AI) researchers claim that they have made great `achievements' in clinical realms. However, clinicians point out the so-called `achievements' have no ability to implement into natural clinical settings. The root cause for this huge gap is that many essential features of natural clinical tasks a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	130,085
2105.15033	DiaKG: an Annotated Diabetes Dataset for Medical Knowledge Graph Construction	Knowledge Graph has been proven effective in modeling structured information and conceptual knowledge, especially in the medical domain. However, the lack of high-quality annotated corpora remains a crucial problem for advancing the research and applications on this task. In order to accelerate the research for domain-...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	237,892
2105.02482	A Unified Pre-training Framework for Conversational AI	In this work, we explore the application of PLATO-2 on various dialogue systems, including open-domain conversation, knowledge grounded dialogue, and task-oriented conversation. PLATO-2 is initially designed as an open-domain chatbot, trained via two-stage curriculum learning. In the first stage, a coarse-grained respo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	233,834
2004.02503	Model-free Data-Driven Computational Mechanics Enhanced by Tensor Voting	The data-driven computing paradigm initially introduced by Kirchdoerfer & Ortiz (2016) is extended by incorporating locally linear tangent spaces into the data set. These tangent spaces are constructed by means of the tensor voting method introduced by Mordohai & Medioni (2010) which improves the learning of the underl...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	171,250
2006.16336	Learning Sparse Prototypes for Text Generation	Prototype-driven text generation uses non-parametric models that first choose from a library of sentence "prototypes" and then modify the prototype to generate the output text. While effective, these methods are inefficient at test time as a result of needing to store and index the entire training corpus. Further, exis...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	184,771
2502.04557	Speeding up Speculative Decoding via Approximate Verification	Speculative Decoding (SD) is a recently proposed technique for faster inference using Large Language Models (LLMs). SD operates by using a smaller draft LLM for autoregressively generating a sequence of tokens and a larger target LLM for parallel verification to ensure statistical consistency. However, periodic paralle...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	531,214
2302.10977	HLSDataset: Open-Source Dataset for ML-Assisted FPGA Design using High Level Synthesis	Machine Learning (ML) has been widely adopted in design exploration using high level synthesis (HLS) to give a better and faster performance, and resource and power estimation at very early stages for FPGA-based design. To perform prediction accurately, high-quality and large-volume datasets are required for training M...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	347,036
2502.09284	SparQLe: Speech Queries to Text Translation Through LLMs	With the growing influence of Large Language Models (LLMs), there is increasing interest in integrating speech representations with them to enable more seamless multi-modal processing and speech understanding. This study introduces a novel approach that leverages self-supervised speech representations in combination wi...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	533,390
2407.09015	Static Analysis of Logic Programs via Boolean Networks	Answer Set Programming (ASP) is a declarative problem solving paradigm that can be used to encode a combinatorial problem as a logic program whose stable models correspond to the solutions of the considered problem. ASP has been widely applied to various domains in AI and beyond. The question "What can be said about st...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	472,412
1809.03839	Unsupervised Domain Adaptation Based on Source-guided Discrepancy	Unsupervised domain adaptation is the problem setting where data generating distributions in the source and target domains are different, and labels in the target domain are unavailable. One important question in unsupervised domain adaptation is how to measure the difference between the source and target domains. A pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	107,417
2101.07579	Spatial Assembly: Generative Architecture With Reinforcement Learning, Self Play and Tree Search	With this work, we investigate the use of Reinforcement Learning (RL) for the generation of spatial assemblies, by combining ideas from Procedural Generation algorithms (Wave Function Collapse algorithm (WFC)) and RL for Game Solving. WFC is a Generative Design algorithm, inspired by Constraint Solving. In WFC, one def...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	216,077
2309.14508	HEROES: Unreal Engine-based Human and Emergency Robot Operation Education System	Training and preparing first responders and humanitarian robots for Mass Casualty Incidents (MCIs) often poses a challenge owing to the lack of realistic and easily accessible test facilities. While such facilities can offer realistic scenarios post an MCI that can serve training and educational purposes for first resp...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	394,635
2305.13398	nnDetection for Intracranial Aneurysms Detection and Localization	Intracranial aneurysms are a commonly occurring and life-threatening condition, affecting approximately 3.2% of the general population. Consequently, detecting these aneurysms plays a crucial role in their management. Lesion detection involves the simultaneous localization and categorization of abnormalities within med...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	366,482
2108.00939	Node repair on connected graphs	We study the problem of erasure correction (node repair) for regenerating codes defined on graphs wherein the cost of transmitting the information to the failed node depends on the graphical distance from this node to the helper vertices of the graph. The information passed to the failed node from the helpers traverses...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	248,875
2305.01140	Geometric Latent Diffusion Models for 3D Molecule Generation	Generative models, especially diffusion models (DMs), have achieved promising results for generating feature-rich geometries and advancing foundational science problems such as molecule design. Inspired by the recent huge success of Stable (latent) Diffusion models, we propose a novel and principled method for 3D molec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,567
2309.04887	SortedAP: Rethinking evaluation metrics for instance segmentation	Designing metrics for evaluating instance segmentation revolves around comprehensively considering object detection and segmentation accuracy. However, other important properties, such as sensitivity, continuity, and equality, are overlooked in the current study. In this paper, we reveal that most existing metrics have...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,888
1401.3667	Group Testing with Prior Statistics	We consider a new group testing model wherein each item is a binary random variable defined by an a priori probability of being defective. We assume that each probability is small and that items are independent, but not necessarily identically distributed. The goal of group testing algorithms is to identify with high p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	29,926
2302.00225	The Past, Current, and Future of Neonatal Intensive Care Units with Artificial Intelligence	Machine learning and deep learning are two subsets of artificial intelligence that involve teaching computers to learn and make decisions from any sort of data. Most recent developments in artificial intelligence are coming from deep learning, which has proven revolutionary in almost all fields, from computer vision to...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	343,148
2411.00404	Fast Adaptation with Kernel and Gradient based Meta Leaning	Model Agnostic Meta Learning or MAML has become the standard for few-shot learning as a meta-learning problem. MAML is simple and can be applied to any model, as its name suggests. However, it often suffers from instability and computational inefficiency during both training and inference times. In this paper, we propo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,582
2305.14831	OD-NeRF: Efficient Training of On-the-Fly Dynamic Neural Radiance Fields	Dynamic neural radiance fields (dynamic NeRFs) have demonstrated impressive results in novel view synthesis on 3D dynamic scenes. However, they often require complete video sequences for training followed by novel view synthesis, which is similar to playing back the recording of a dynamic 3D scene. In contrast, we prop...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	367,284
2309.00742	Learning Robust Model Predictive Control for Voltage Control of Islanded Microgrid	This paper proposes a novel control design for voltage tracking of an islanded AC microgrid in the presence of {nonlinear} loads and parametric uncertainties at the primary level of control. The proposed method is based on the Tube-Based Robust Model Predictive Control (RMPC), an online optimization-based method which ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	389,403
1806.07174	FRnet-DTI: Deep Convolutional Neural Networks with Evolutionary and Structural Features for Drug-Target Interaction	The task of drug-target interaction prediction holds significant importance in pharmacology and therapeutic drug design. In this paper, we present FRnet-DTI, an auto encoder and a convolutional classifier for feature manipulation and drug target interaction prediction. Two convolutional neural neworks are proposed wher...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	100,859
2407.17157	Establishing Causal Relationship Between Whole Slide Image Predictions and Diagnostic Evidence Subregions in Deep Learning	Due to the lack of fine-grained annotation guidance, current Multiple Instance Learning (MIL) struggles to establish a robust causal relationship between Whole Slide Image (WSI) diagnosis and evidence sub-images, just like fully supervised learning. So many noisy images can undermine the network's prediction. The propo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	475,864
2404.01240	AURORA: Navigating UI Tarpits via Automated Neural Screen Understanding	Nearly a decade of research in software engineering has focused on automating mobile app testing to help engineers in overcoming the unique challenges associated with the software platform. Much of this work has come in the form of Automated Input Generation tools (AIG tools) that dynamically explore app screens. Howev...	true	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	true	443,330
2110.03545	Privacy-Preserving Coded Mobile Edge Computing for Low-Latency Distributed Inference	We consider a mobile edge computing scenario where a number of devices want to perform a linear inference $\boldsymbol{W}\boldsymbol{x}$ on some local data $\boldsymbol{x}$ given a network-side matrix $\boldsymbol{W}$. The computation is performed at the network edge over a number of edge servers. We propose a coding s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	259,538
1905.10700	Tell Me About Yourself: Using an AI-Powered Chatbot to Conduct Conversational Surveys with Open-ended Questions	The rise of increasingly more powerful chatbots offers a new way to collect information through conversational surveys, where a chatbot asks open-ended questions, interprets a user's free-text responses, and probes answers whenever needed. To investigate the effectiveness and limitations of such a chatbot in conducting...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	132,158
2004.11135	Age-of-Information with Information Source Diversity in an Energy Harvesting System	Age of information (AoI) is one of the key performance metrics for Internet of things (IoT) systems. Timely status updates are essential for many IoT applications; however, they are subject to strict constraints related on the available energy and unreliability of underlying information sources. Hence, the scheduling o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	173,824
2007.03220	Sapphire: Automatic Configuration Recommendation for Distributed Storage Systems	Modern distributed storage systems come with aplethora of configurable parameters that controlmodule behavior and affect system performance. Default settings provided by developers are often suboptimal for specific user cases. Tuning parameters can provide significant performance gains but is a difficult task requiring...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	185,993
2304.11947	Towards Top-$K$ Non-Overlapping Sequential Patterns	Sequential pattern mining (SPM) has excellent prospects and application spaces and has been widely used in different fields. The non-overlapping SPM, as one of the data mining techniques, has been used to discover patterns that have requirements for gap constraints in some specific mining tasks, such as bio-data mining...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	360,030
1707.08621	Communication versus Computation: Duality for multiple access channels and source coding	Computation codes in network information theory are designed for the scenarios where the decoder is not interested in recovering the information sources themselves, but only a function thereof. K\"orner and Marton showed for distributed source coding that such function decoding can be achieved more efficiently than dec...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	77,862
2310.09693	Study on the Time Domain Precision Evolution Mechanism of CNC Machine Tool Feed Systems Based on Acceleration and Deceleration Capability Indicator	The escalating demand for high-speed and high-precision machining in machine tool feed system has brought to the forefront the challenge of its design method. Currently, existing methodologies struggle to ascertain compliance with dynamic performance requirements during the design phase, often resulting in either exces...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	399,899
2211.13503	Optimization of Humanoid Robot Designs for Human-Robot Ergonomic Payload Lifting	When a human and a humanoid robot collaborate physically, ergonomics is a key factor to consider. Assuming a given humanoid robot, several control architectures exist nowadays to address ergonomic physical human-robot collaboration. This paper takes one step further by considering robot hardware parameters as optimizat...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	332,499
1902.00768	Learning Linear Dynamical Systems with Semi-Parametric Least Squares	We analyze a simple prefiltered variation of the least squares estimator for the problem of estimation with biased, semi-parametric noise, an error model studied more broadly in causal statistics and active learning. We prove an oracle inequality which demonstrates that this procedure provably mitigates the variance in...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	120,504
1607.04813	Infinite families of 2-designs and 3-designs from linear codes	The interplay between coding theory and $t$-designs started many years ago. While every $t$-design yields a linear code over every finite field, the largest $t$ for which an infinite family of $t$-designs is derived directly from a linear or nonlinear code is $t=3$. Sporadic $4$-designs and $5$-designs were derived fro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	58,670
2407.05106	DailyDVS-200: A Comprehensive Benchmark Dataset for Event-Based Action Recognition	Neuromorphic sensors, specifically event cameras, revolutionize visual data acquisition by capturing pixel intensity changes with exceptional dynamic range, minimal latency, and energy efficiency, setting them apart from conventional frame-based cameras. The distinctive capabilities of event cameras have ignited signif...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,824
1904.03516	Instance-Level Meta Normalization	This paper presents a normalization mechanism called Instance-Level Meta Normalization (ILM~Norm) to address a learning-to-normalize problem. ILM~Norm learns to predict the normalization parameters via both the feature feed-forward and the gradient back-propagation paths. ILM~Norm provides a meta normalization mechanis...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	126,750
2502.05049	On the Inference of Sociodemographics on Reddit	Inference of sociodemographic attributes of social media users is an essential step for computational social science (CSS) research to link online and offline behavior. However, there is a lack of a systematic evaluation and clear guidelines for optimal methodologies for this task on Reddit, one of today's largest soci...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	531,418
2302.09228	Web Photo Source Identification based on Neural Enhanced Camera Fingerprint	With the growing popularity of smartphone photography in recent years, web photos play an increasingly important role in all walks of life. Source camera identification of web photos aims to establish a reliable linkage from the captured images to their source cameras, and has a broad range of applications, such as ima...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	346,331
2011.12953	Unsupervised Object Detection with LiDAR Clues	Despite the importance of unsupervised object detection, to the best of our knowledge, there is no previous work addressing this problem. One main issue, widely known to the community, is that object boundaries derived only from 2D image appearance are ambiguous and unreliable. To address this, we exploit LiDAR clues t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	208,324
1703.04565	Fuzzy Model Tree For Early Effort Estimation	Use Case Points (UCP) is a well-known method to estimate the project size, based on Use Case diagram, at early phases of software development. Although the Use Case diagram is widely accepted as a de-facto model for analyzing object oriented software requirements over the world, UCP method did not take sufficient amoun...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	69,919
2305.17680	Evaluating GPT-3 Generated Explanations for Hateful Content Moderation	Recent research has focused on using large language models (LLMs) to generate explanations for hate speech through fine-tuning or prompting. Despite the growing interest in this area, these generated explanations' effectiveness and potential limitations remain poorly understood. A key concern is that these explanations...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	368,702
1611.06962	Sampled Image Tagging and Retrieval Methods on User Generated Content	Traditional image tagging and retrieval algorithms have limited value as a result of being trained with heavily curated datasets. These limitations are most evident when arbitrary search words are used that do not intersect with training set labels. Weak labels from user generated content (UGC) found in the wild (e.g.,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	64,285
1201.0490	Scikit-learn: Machine Learning in Python	Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	13,664
2003.04676	Deep Hough Transform for Semantic Line Detection	We focus on a fundamental task of detecting meaningful line structures, a.k.a. semantic line, in natural scenes. Many previous methods regard this problem as a special case of object detection and adjust existing object detectors for semantic line detection. However, these methods neglect the inherent characteristics o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	167,618
2301.10863	Shape Reconstruction from Thoracoscopic Images using Self-supervised Virtual Learning	Intraoperative shape reconstruction of organs from endoscopic camera images is a complex yet indispensable technique for image-guided surgery. To address the uncertainty in reconstructing entire shapes from single-viewpoint occluded images, we propose a framework for generative virtual learning of shape reconstruction ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	341,927
1602.02722	PAC Reinforcement Learning with Rich Observations	We propose and study a new model for reinforcement learning with rich observations, generalizing contextual bandits to sequential decision making. These models require an agent to take actions based on observations (features) with the goal of achieving long-term performance competitive with a large set of policies. To ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	51,904
2107.12706	Improving ClusterGAN Using Self-Augmented Information Maximization of Disentangling Latent Spaces	Since their introduction in the last few years, conditional generative models have seen remarkable achievements. However, they often need the use of large amounts of labelled information. By using unsupervised conditional generation in conjunction with a clustering inference network, ClusterGAN has recently been able t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	247,988
1403.2004	Natural Language Feature Selection via Cooccurrence	Specificity is important for extracting collocations, keyphrases, multi-word and index terms [Newman et al. 2012]. It is also useful for tagging, ontology construction [Ryu and Choi 2006], and automatic summarization of documents [Louis and Nenkova 2011, Chali and Hassan 2012]. Term frequency and inverse-document frequ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	31,450
2311.18198	S-T CRF: Spatial-Temporal Conditional Random Field for Human Trajectory Prediction	Trajectory prediction is of significant importance in computer vision. Accurate pedestrian trajectory prediction benefits autonomous vehicles and robots in planning their motion. Pedestrians' trajectories are greatly influenced by their intentions. Prior studies having introduced various deep learning methods only pay ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,595
1906.05274	Efficient Exploration via State Marginal Matching	Exploration is critical to a reinforcement learning agent's performance in its given environment. Prior exploration methods are often based on using heuristic auxiliary predictions to guide policy behavior, lacking a mathematically-grounded objective with clear properties. In contrast, we recast exploration as a proble...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	134,981
2308.02150	Learning to Shape by Grinding: Cutting-surface-aware Model-based Reinforcement Learning	Object shaping by grinding is a crucial industrial process in which a rotating grinding belt removes material. Object-shape transition models are essential to achieving automation by robots; however, learning such a complex model that depends on process conditions is challenging because it requires a significant amount...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	383,510
2211.16585	DSO-DERA Coordination for the Wholesale Market Participation of Distributed Energy Resources	We design a coordination mechanism between a distribution system operator (DSO) and distributed energy resource aggregators (DERAs) participating directly in the wholesale electricity market. Aimed at ensuring system reliability while providing open access to DERAs, the coordination mechanism includes a forward auction...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	333,673
2201.01633	Adaptive Online Incremental Learning for Evolving Data Streams	Recent years have witnessed growing interests in online incremental learning. However, there are three major challenges in this area. The first major difficulty is concept drift, that is, the probability distribution in the streaming data would change as the data arrives. The second major difficulty is catastrophic for...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	274,308
2110.03028	Reconsidering Optimistic Algorithms for Relational DBMS	At DBKDA 2019, we demonstrated that StrongDBMS with simple but rigorous optimistic algorithms, provides better performance in situations of high concurrency than major commercial database management systems (DBMS). The demonstration was convincing but the reasons for its success were not fully analysed. There is a brie...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	259,336
2203.04446	Self-Supervised Domain Calibration and Uncertainty Estimation for Place Recognition	Visual place recognition techniques based on deep learning, which have imposed themselves as the state-of-the-art in recent years, do not generalize well to environments visually different from the training set. Thus, to achieve top performance, it is sometimes necessary to fine-tune the networks to the target environm...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	284,474
1510.08490	Psychological Determinants and Consequences of Complex Networks	This paper presents two models that exemplify psychological factors as a determinant and as a consequence of social network characteristics. There is an endogeneity considered in network formation: while the social experiences have impacts on people, their current psychological states and traits affect network evolutio...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	48,290
2211.12571	"Coherent Mode" for the World's Public Square	Systems for large scale deliberation have resolved polarized issues and shifted agenda setting into the public's hands. These systems integrate bridging-based ranking algorithms - including group informed consensus implemented in Polis and the continuous matrix factorization approach implemented by Twitter Birdwatch - ...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	332,157
cs/0106015	Organizing Encyclopedic Knowledge based on the Web and its Application to Question Answering	We propose a method to generate large-scale encyclopedic knowledge, which is valuable for much NLP research, based on the Web. We first search the Web for pages containing a term in question. Then we use linguistic patterns and HTML structures to extract text fragments describing the term. Finally, we organize extracte...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,355
1207.3510	HMRF-EM-image: Implementation of the Hidden Markov Random Field Model and its Expectation-Maximization Algorithm	In this project, we study the hidden Markov random field (HMRF) model and its expectation-maximization (EM) algorithm. We implement a MATLAB toolbox named HMRF-EM-image for 2D image segmentation using the HMRF-EM framework. This toolbox also implements edge-prior-preserving image segmentation, and can be easily reconfi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	17,479
2212.09273	Learning Object-level Point Augmentor for Semi-supervised 3D Object Detection	Semi-supervised object detection is important for 3D scene understanding because obtaining large-scale 3D bounding box annotations on point clouds is time-consuming and labor-intensive. Existing semi-supervised methods usually employ teacher-student knowledge distillation together with an augmentation strategy to lever...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	337,056
2009.05660	Abstract Neural Networks	Deep Neural Networks (DNNs) are rapidly being applied to safety-critical domains such as drone and airplane control, motivating techniques for verifying the safety of their behavior. Unfortunately, DNN verification is NP-hard, with current algorithms slowing exponentially with the number of nodes in the DNN. This paper...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	195,377
2203.09692	Facial Geometric Detail Recovery via Implicit Representation	Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries through facial prior while learning details as additional displacement maps or personalized basis. However, these techniques typically require ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,246
2311.03974	NOMA Enabled Multi-Access Edge Computing: A Joint MU-MIMO Precoding and Computation Offloading Design	This letter investigates computation offloading and transmit precoding co-design for multi-access edge computing (MEC), where multiple MEC users (MUs) equipped with multiple antennas access the MEC server in a non-orthogonal multiple access manner. We aim to minimize the total energy consumption of all MUs while satisf...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	406,054
1610.05890	Global Exponential Stabilization of Acyclic Traffic Networks	This work is devoted to the construction of explicit feedback control laws for the robust, global, exponential stabilization of general, uncertain, discrete-time, acyclic traffic networks. We consider discrete-time, uncertain network models which satisfy very weak assumptions. The construction of the controllers and th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	62,579

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