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
1704.02641	Quantized Innovations Bayesian Filtering	The paper provides simple formulas of Bayesian filtering for the exact recursive computation of state conditional probability density functions given quantized innovations signal measurements of a linear stochastic system. This is a topic of current interest because the innovations signal should be white and therefore ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	71,485
2004.01218	General Identification of Dynamic Treatment Regimes Under Interference	In many applied fields, researchers are often interested in tailoring treatments to unit-level characteristics in order to optimize an outcome of interest. Methods for identifying and estimating treatment policies are the subject of the dynamic treatment regime literature. Separately, in many settings the assumption th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	170,848
2301.06732	Predictive Modeling of Coronal Hole Areas Using Long Short-Term Memory Networks	In the era of space exploration, the implications of space weather have become increasingly evident. Central to this is the phenomenon of coronal holes, which can significantly influence the functioning of satellites and aircraft. These coronal holes, present on the sun, are distinguished by their open magnetic field l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	340,725
2104.07240	Learning Regional Attention over Multi-resolution Deep Convolutional Features for Trademark Retrieval	Large-scale trademark retrieval is an important content-based image retrieval task. A recent study shows that off-the-shelf deep features aggregated with Regional-Maximum Activation of Convolutions (R-MAC) achieve state-of-the-art results. However, R-MAC suffers in the presence of background clutter/trivial regions and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	230,346
2306.01163	A Multi-Modal Latent-Features based Service Recommendation System for the Social Internet of Things	The Social Internet of Things (SIoT), is revolutionizing how we interact with our everyday lives. By adding the social dimension to connecting devices, the SIoT has the potential to drastically change the way we interact with smart devices. This connected infrastructure allows for unprecedented levels of convenience, a...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	370,322
1801.01681	VulDeePecker: A Deep Learning-Based System for Vulnerability Detection	The automatic detection of software vulnerabilities is an important research problem. However, existing solutions to this problem rely on human experts to define features and often miss many vulnerabilities (i.e., incurring high false negative rate). In this paper, we initiate the study of using deep learning-based vul...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	87,778
1205.6024	A Social Influence Model Based On Circuit Theory	Understanding the behaviors of information propagation is essential for the effective exploitation of social influence in social networks. However, few existing influence models are tractable and efficient for describing the information propagation process, especially when dealing with the difficulty of incorporating t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	16,201
1712.02066	Automatic Segmentation and Overall Survival Prediction in Gliomas using Fully Convolutional Neural Network and Texture Analysis	In this paper, we use a fully convolutional neural network (FCNN) for the segmentation of gliomas from Magnetic Resonance Images (MRI). A fully automatic, voxel based classification was achieved by training a 23 layer deep FCNN on 2-D slices extracted from patient volumes. The network was trained on slices extracted fr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	86,233
2107.10997	Resource Efficient Mountainous Skyline Extraction using Shallow Learning	Skyline plays a pivotal role in mountainous visual geo-localization and localization/navigation of planetary rovers/UAVs and virtual/augmented reality applications. We present a novel mountainous skyline detection approach where we adapt a shallow learning approach to learn a set of filters to discriminate between edge...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	247,462
2309.17205	Towards Complex-query Referring Image Segmentation: A Novel Benchmark	Referring Image Understanding (RIS) has been extensively studied over the past decade, leading to the development of advanced algorithms. However, there has been a lack of research investigating how existing algorithms should be benchmarked with complex language queries, which include more informative descriptions of s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	395,680
1304.3103	Learning Link-Probabilities in Causal Trees	A learning algorithm is presented which given the structure of a causal tree, will estimate its link probabilities by sequential measurements on the leaves only. Internal nodes of the tree represent conceptual (hidden) variables inaccessible to observation. The method described is incremental, local, efficient, and rem...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,819
2312.07168	Equivariant Flow Matching with Hybrid Probability Transport	The generation of 3D molecules requires simultaneously deciding the categorical features~(atom types) and continuous features~(atom coordinates). Deep generative models, especially Diffusion Models (DMs), have demonstrated effectiveness in generating feature-rich geometries. However, existing DMs typically suffer from ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	414,822
2410.09375	Looped ReLU MLPs May Be All You Need as Practical Programmable Computers	Previous work has demonstrated that attention mechanisms are Turing complete. More recently, it has been shown that a looped 9-layer Transformer can function as a universal programmable computer. In contrast, the multi-layer perceptrons with $\mathsf{ReLU}$ activation ($\mathsf{ReLU}$-$\mathsf{MLP}$), one of the most f...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	497,564
2109.13456	SiamEvent: Event-based Object Tracking via Edge-aware Similarity Learning with Siamese Networks	Event cameras are novel sensors that perceive the per-pixel intensity changes and output asynchronous event streams, showing lots of advantages over traditional cameras, such as high dynamic range (HDR) and no motion blur. It has been shown that events alone can be used for object tracking by motion compensation or pre...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	257,644
2306.14055	Transforming a Quadruped into a Guide Robot for the Visually Impaired: Formalizing Wayfinding, Interaction Modeling, and Safety Mechanism	This paper explores the principles for transforming a quadrupedal robot into a guide robot for individuals with visual impairments. A guide robot has great potential to resolve the limited availability of guide animals that are accessible to only two to three percent of the potential blind or visually impaired (BVI) us...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	375,519
1910.00424	AV Speech Enhancement Challenge using a Real Noisy Corpus	This paper presents, a first of its kind, audio-visual (AV) speech enhacement challenge in real-noisy settings. A detailed description of the AV challenge, a novel real noisy AV corpus (ASPIRE), benchmark speech enhancement task, and baseline performance results are outlined. The latter are based on training a deep neu...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	147,661
2001.03253	Campfire: Compressible, Regularization-Free, Structured Sparse Training for Hardware Accelerators	This paper studies structured sparse training of CNNs with a gradual pruning technique that leads to fixed, sparse weight matrices after a set number of epochs. We simplify the structure of the enforced sparsity so that it reduces overhead caused by regularization. The proposed training methodology Campfire explores pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	159,922
2303.08914	MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language Knowledge	Large scale Vision-Language (VL) models have shown tremendous success in aligning representations between visual and text modalities. This enables remarkable progress in zero-shot recognition, image generation & editing, and many other exciting tasks. However, VL models tend to over-represent objects while paying much ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,821
2501.12927	Longitudinal Missing Data Imputation for Predicting Disability Stage of Patients with Multiple Sclerosis	Multiple Sclerosis (MS) is a chronic disease characterized by progressive or alternate impairment of neurological functions (motor, sensory, visual, and cognitive). Predicting disease progression with a probabilistic and time-dependent approach might help in suggesting interventions that can delay the progression of th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	526,488
2103.05041	Advances in Inference and Representation for Simultaneous Localization and Mapping	Simultaneous localization and mapping (SLAM) is the process of constructing a global model of an environment from local observations of it; this is a foundational capability for mobile robots, supporting such core functions as planning, navigation, and control. This article reviews recent progress in SLAM, focusing on ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	223,833
2011.12049	Non-Invertible-Element Constacyclic Codes over Finite PIRs	In this paper we introduce the notion of $\lambda$-constacyclic codes over finite rings $R$ for arbitary element $\lambda$ of $R$. We study the non-invertible-element constacyclic codes (NIE-constacyclic codes) over finite principal ideal rings (PIRs). We determine the algebraic structures of all NIE-constacyclic codes...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	208,035
1403.0052	TBX goes TEI -- Implementing a TBX basic extension for the Text Encoding Initiative guidelines	This paper presents an attempt to customise the TEI (Text Encoding Initiative) guidelines in order to offer the possibility to incorporate TBX (TermBase eXchange) based terminological entries within any kind of TEI documents. After presenting the general historical, conceptual and technical contexts, we describe the va...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	31,259
1903.10929	TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo	One of the most successful approaches in Multi-View Stereo estimates a depth map and a normal map for each view via PatchMatch-based optimization and fuses them into a consistent 3D points cloud. This approach relies on photo-consistency to evaluate the goodness of a depth estimate. It generally produces very accurate ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	125,395
2309.02396	Black-Box Attacks against Signed Graph Analysis via Balance Poisoning	Signed graphs are well-suited for modeling social networks as they capture both positive and negative relationships. Signed graph neural networks (SGNNs) are commonly employed to predict link signs (i.e., positive and negative) in such graphs due to their ability to handle the unique structure of signed graphs. However...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	390,025
2004.05653	Guided Policy Improvement for Satisfying STL Tasks using Funnel Adaptation	We introduce a sampling-based learning method for solving optimal control problems involving task satisfaction constraints for systems with partially known dynamics. The control problems are defined by a cost to be minimized and a task to be satisfied, given in the language of signal temporal logic (STL). The complex n...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	172,264
2006.03659	DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations	Sentence embeddings are an important component of many natural language processing (NLP) systems. Like word embeddings, sentence embeddings are typically learned on large text corpora and then transferred to various downstream tasks, such as clustering and retrieval. Unlike word embeddings, the highest performing solut...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	180,387
2201.05562	Investigation of Data Augmentation Techniques for Disordered Speech Recognition	Disordered speech recognition is a highly challenging task. The underlying neuro-motor conditions of people with speech disorders, often compounded with co-occurring physical disabilities, lead to the difficulty in collecting large quantities of speech required for system development. This paper investigates a set of d...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	275,423
1109.6717	Lamarckism and mechanism synthesis: approaching constrained optimization with ideas from biology	Nonlinear constrained optimization problems are encountered in many scientific fields. To utilize the huge calculation power of current computers, many mathematic models are also rebuilt as optimization problems. Most of them have constrained conditions which need to be handled. Borrowing biological concepts, a study i...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	12,408
2409.20498	Enhancing Romanian Offensive Language Detection through Knowledge Distillation, Multi-Task Learning, and Data Augmentation	This paper highlights the significance of natural language processing (NLP) within artificial intelligence, underscoring its pivotal role in comprehending and modeling human language. Recent advancements in NLP, particularly in conversational bots, have garnered substantial attention and adoption among developers. This...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	493,142
2201.12263	RiskNet: Neural Risk Assessment in Networks of Unreliable Resources	We propose a graph neural network (GNN)-based method to predict the distribution of penalties induced by outages in communication networks, where connections are protected by resources shared between working and backup paths. The GNN-based algorithm is trained only with random graphs generated with the Barab\'asi-Alber...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	277,579
2212.04257	Momentum Calibration for Text Generation	The input and output of most text generation tasks can be transformed to two sequences of tokens and they can be modeled using sequence-to-sequence learning modeling tools such as Transformers. These models are usually trained by maximizing the likelihood the output text sequence and assumes the input sequence and all ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	335,381
2003.00598	Data Normalization for Bilinear Structures in High-Frequency Financial Time-series	Financial time-series analysis and forecasting have been extensively studied over the past decades, yet still remain as a very challenging research topic. Since the financial market is inherently noisy and stochastic, a majority of financial time-series of interests are non-stationary, and often obtained from different...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	166,340
2204.09105	An improved central limit theorem and fast convergence rates for entropic transportation costs	We prove a central limit theorem for the entropic transportation cost between subgaussian probability measures, centered at the population cost. This is the first result which allows for asymptotically valid inference for entropic optimal transport between measures which are not necessarily discrete. In the compactly s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	292,316
1809.01822	Driving Experience Transfer Method for End-to-End Control of Self-Driving Cars	In this paper, we present a transfer learning method for the end-to-end control of self-driving cars, which enables a convolutional neural network (CNN) trained on a source domain to be utilized for the same task in a different target domain. A conventional CNN for the end-to-end control is designed to map a single fro...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	106,902
2304.09944	\"Uberpr\"ufung von Integrit\"atsbedingungen in Deduktiven Datenbanken	Advancements in computer science and AI lead to the development of larger, more complex knowledge bases. These are susceptible to contradictions, particularly when multiple experts are involved. To ensure integrity during changes, procedures are needed. This work addresses the problem from a logical programming perspec...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	359,230
2002.11934	Supervised Dimensionality Reduction and Visualization using Centroid-encoder	Visualizing high-dimensional data is an essential task in Data Science and Machine Learning. The Centroid-Encoder (CE) method is similar to the autoencoder but incorporates label information to keep objects of a class close together in the reduced visualization space. CE exploits nonlinearity and labels to encode high ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	165,885
2009.07719	Domain-invariant Similarity Activation Map Contrastive Learning for Retrieval-based Long-term Visual Localization	Visual localization is a crucial component in the application of mobile robot and autonomous driving. Image retrieval is an efficient and effective technique in image-based localization methods. Due to the drastic variability of environmental conditions, e.g. illumination, seasonal and weather changes, retrieval-based ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	196,026
1610.09606	Impedance control of a cable-driven series elastic actuator with the 2-DOF control structure	Series elastic actuators (SEAs) are growingly important in physical human-robot interaction (HRI) due to their inherent safety and compliance. Cable-driven SEAs also allow flexible installation and remote torque transmission, etc. However, there are still challenges for the impedance control of cable-driven SEAs, such ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	63,088
1702.05899	An Examination of the Benefits of Scalable TTI for Heterogeneous Traffic Management in 5G Networks	The rapid growth in the number and variety of connected devices requires 5G wireless systems to cope with a very heterogeneous traffic mix. As a consequence, the use of a fixed TTI during transmission is not necessarily the most efficacious method when heterogeneous traffic types need to be simultaneously serviced.This...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	68,496
2409.19703	Applying the Lower-Biased Teacher Model in Semi-Supervised Object Detection	I present the Lower Biased Teacher model, an enhancement of the Unbiased Teacher model, specifically tailored for semi-supervised object detection tasks. The primary innovation of this model is the integration of a localization loss into the teacher model, which significantly improves the accuracy of pseudo-label gener...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	492,812
1512.02615	On Variational Expressions for Quantum Relative Entropies	Distance measures between quantum states like the trace distance and the fidelity can naturally be defined by optimizing a classical distance measure over all measurement statistics that can be obtained from the respective quantum states. In contrast, Petz showed that the measured relative entropy, defined as a maximiz...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	49,955
2309.12365	An Efficient Intelligent Semi-Automated Warehouse Inventory Stocktaking System	In the context of evolving supply chain management, the significance of efficient inventory management has grown substantially for businesses. However, conventional manual and experience-based approaches often struggle to meet the complexities of modern market demands. This research introduces an intelligent inventory ...	true	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	393,776
2407.10844	Improved Uncertainty Estimation of Graph Neural Network Potentials Using Engineered Latent Space Distances	Graph neural networks (GNNs) have been shown to be astonishingly capable models for molecular property prediction, particularly as surrogates for expensive density functional theory calculations of relaxed energy for novel material discovery. However, one limitation of GNNs in this context is the lack of useful uncerta...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	473,155
1910.10871	Preventing Adversarial Use of Datasets through Fair Core-Set Construction	We propose improving the privacy properties of a dataset by publishing only a strategically chosen "core-set" of the data containing a subset of the instances. The core-set allows strong performance on primary tasks, but forces poor performance on unwanted tasks. We give methods for both linear models and neural networ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	150,613
2209.01683	Learning to Predict Fitness for Duty using Near Infrared Periocular Iris Images	This research proposes a new database and method to detect the reduction of alertness conditions due to alcohol, drug consumption and sleepiness deprivation from Near-Infra-Red (NIR) periocular eye images. The study focuses on determining the effect of external factors on the Central Nervous System (CNS). The goal is t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	315,978
2406.08624	A Sublinear Algorithm for Approximate Shortest Paths in Large Networks	Computing distances and finding shortest paths in massive real-world networks is a fundamental algorithmic task in network analysis. There are two main approaches to solving this task. On one hand are traversal-based algorithms like bidirectional breadth-first search (BiBFS) with no preprocessing step and slow individu...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	463,553
1607.03272	Performance and Complexity Analysis of a Reduced Iterations LLL Algorithm	Multiple-input multiple-output (MIMO) systems are playing an increasing and interesting role in the recent wireless communication. The complexity and the performance of the systems are driving the different studies and researches. Lattices Reduction techniques bring more resources to investigate the complexity and perf...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	58,482
1610.02482	4D Crop Monitoring: Spatio-Temporal Reconstruction for Agriculture	Autonomous crop monitoring at high spatial and temporal resolution is a critical problem in precision agriculture. While Structure from Motion and Multi-View Stereo algorithms can finely reconstruct the 3D structure of a field with low-cost image sensors, these algorithms fail to capture the dynamic nature of continuou...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	62,105
1202.1595	Signal Recovery on Incoherent Manifolds	Suppose that we observe noisy linear measurements of an unknown signal that can be modeled as the sum of two component signals, each of which arises from a nonlinear sub-manifold of a high dimensional ambient space. We introduce SPIN, a first order projected gradient method to recover the signal components. Despite the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	14,210
2210.08168	MKIS-Net: A Light-Weight Multi-Kernel Network for Medical Image Segmentation	Image segmentation is an important task in medical imaging. It constitutes the backbone of a wide variety of clinical diagnostic methods, treatments, and computer-aided surgeries. In this paper, we propose a multi-kernel image segmentation net (MKIS-Net), which uses multiple kernels to create an efficient receptive fie...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	324,019
1612.05605	Use of Signed Permutations in Cryptography	In this paper we consider cryptographic applications of the arithmetic on the hyperoctahedral group. On an appropriate subgroup of the latter, we particularly propose to construct public key cryptosystems based on the discrete logarithm. The fact that the group of signed permutations has rich properties provides fast a...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	65,706
2404.07973	Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models	While Ferret seamlessly integrates regional understanding into the Large Language Model (LLM) to facilitate its referring and grounding capability, it poses certain limitations: constrained by the pre-trained fixed visual encoder and failed to perform well on broader tasks. In this work, we unveil Ferret-v2, a signific...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	446,052
1812.01532	Control of automated guided vehicles without collision by quantum annealer and digital devices	We formulate an optimization problem to control a large number of automated guided vehicles in a plant without collision. The formulation consists of binary variables. A quadratic cost function over these variables enables us to utilize certain solvers on digital computers and recently developed purpose-specific hardwa...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	115,544
1902.00750	How to Write High-quality News on Social Network? Predicting News Quality by Mining Writing Style	Rapid development of Internet technologies promotes traditional newspapers to report news on social networks. However, people on social networks may have different needs which naturally arises the question: whether can we analyze the influence of writing style on news quality automatically and assist writers in improvi...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	120,496
2104.08825	Flexible Generation of Natural Language Deductions	An interpretable system for open-domain reasoning needs to express its reasoning process in a transparent form. Natural language is an attractive representation for this purpose -- it is both highly expressive and easy for humans to understand. However, manipulating natural language statements in logically consistent w...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	231,003
2109.02740	Single-Camera 3D Head Fitting for Mixed Reality Clinical Applications	We address the problem of estimating the shape of a person's head, defined as the geometry of the complete head surface, from a video taken with a single moving camera, and determining the alignment of the fitted 3D head for all video frames, irrespective of the person's pose. 3D head reconstructions commonly tend to f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	253,835
2112.03358	Associative Memories Using Complex-Valued Hopfield Networks Based on Spin-Torque Oscillator Arrays	Simulations of complex-valued Hopfield networks based on spin-torque oscillators can recover phase-encoded images. Sequences of memristor-augmented inverters provide tunable delay elements that implement complex weights by phase shifting the oscillatory output of the oscillators. Pseudo-inverse training suffices to sto...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	270,168
nlin/0609033	Fame Emerges as a Result of Small Memory	A dynamic memory model is proposed in which an agent ``learns'' a new agent by means of recommendation. The agents can also ``remember'' and ``forget''. The memory size is decreased while the population size is kept constant. ``Fame'' emerged as a few agents become very well known in expense of the majority being compl...	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	540,792
1603.07010	Practical Encoder and Decoder for Power Constrained QC-LDPC lattices	LDPC lattices were the first family of lattices that equipped with iterative decoding algorithms under which they perform very well in high dimensions. In this paper, we introduce quasi cyclic low density parity check (QC-LDPC) lattices as a special case of LDPC lattices with one binary QC-LDPC code as their underlying...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	53,573
2502.11244	Soteria: Language-Specific Functional Parameter Steering for Multilingual Safety Alignment	Ensuring consistent safety across multiple languages remains a significant challenge for large language models (LLMs). We introduce Soteria, a lightweight yet powerful strategy that locates and minimally adjusts the "functional heads" most responsible for harmful content generation in each language. By altering only a ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	534,265
2403.06112	Decentralized P2P Trading based on Blockchain for Retail Electricity Markets	This paper introduces peer to peer (P2P) trading mechanisms based on decentralized Blockchain to facilitate retail electricity market for ever-increasing distributed energy resources (DERs). The Blockchain network supports fast and secure retail trading among DERs and facilitates a sustainable local P2P trading platfor...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	436,308
2203.13224	Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion	Language models (LMs) have recently been shown to generate more factual responses by employing modularity (Zhou et al., 2021) in combination with retrieval (Adolphs et al., 2021). We extend the recent approach of Adolphs et al. (2021) to include internet search as a module. Our SeeKeR (Search engine->Knowledge->Respons...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	287,545
2411.00156	Unlocking the Potential of Global Human Expertise	Solving societal problems on a global scale requires the collection and processing of ideas and methods from diverse sets of international experts. As the number and diversity of human experts increase, so does the likelihood that elements in this collective knowledge can be combined and refined to discover novel and b...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	false	false	504,457
2406.17707	SurgeMOD: Translating image-space tissue motions into vision-based surgical forces	We present a new approach for vision-based force estimation in Minimally Invasive Robotic Surgery based on frequency domain basis of motion of organs derived directly from video. Using internal movements generated by natural processes like breathing or the cardiac cycle, we infer the image-space basis of the motion on ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	467,686
1702.01313	Cluster-based Kriging Approximation Algorithms for Complexity Reduction	Kriging or Gaussian Process Regression is applied in many fields as a non-linear regression model as well as a surrogate model in the field of evolutionary computation. However, the computational and space complexity of Kriging, that is cubic and quadratic in the number of data points respectively, becomes a major bott...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	67,791
1305.5765	Gray codes and Enumerative Coding for vector spaces	Gray codes for vector spaces are considered in two graphs: the Grassmann graph, and the projective-space graph, both of which have recently found applications in network coding. For the Grassmann graph, constructions of cyclic optimal codes are given for all parameters. As for the projective-space graph, two constructi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	24,786
2103.16827	Integer-only Zero-shot Quantization for Efficient Speech Recognition	End-to-end neural network models achieve improved performance on various automatic speech recognition (ASR) tasks. However, these models perform poorly on edge hardware due to large memory and computation requirements. While quantizing model weights and/or activations to low-precision can be a promising solution, previ...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	227,718
2105.03166	A Bayesian model of information cascades	An information cascade is a circumstance where agents make decisions in a sequential fashion by following other agents. Bikhchandani et al., predict that once a cascade starts it continues, even if it is wrong, until agents receive an external input such as public information. In an information cascade, even if an agen...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	234,063
2103.00742	Automated Machine Learning on Graphs: A Survey	Machine learning on graphs has been extensively studied in both academic and industry. However, as the literature on graph learning booms with a vast number of emerging methods and techniques, it becomes increasingly difficult to manually design the optimal machine learning algorithm for different graph-related tasks. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	222,381
2106.01441	Optimization of Heterogeneous Systems with AI Planning Heuristics and Machine Learning: A Performance and Energy Aware Approach	Heterogeneous computing systems provide high performance and energy efficiency. However, to optimally utilize such systems, solutions that distribute the work across host CPUs and accelerating devices are needed. In this paper, we present a performance and energy aware approach that combines AI planning heuristics for ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	238,494
2106.08148	Weakly-Supervised Photo-realistic Texture Generation for 3D Face Reconstruction	Although much progress has been made recently in 3D face reconstruction, most previous work has been devoted to predicting accurate and fine-grained 3D shapes. In contrast, relatively little work has focused on generating high-fidelity face textures. Compared with the prosperity of photo-realistic 2D face image generat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	241,199
1905.10708	Underwater Fish Detection with Weak Multi-Domain Supervision	Given a sufficiently large training dataset, it is relatively easy to train a modern convolution neural network (CNN) as a required image classifier. However, for the task of fish classification and/or fish detection, if a CNN was trained to detect or classify particular fish species in particular background habitats, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	132,163
2110.12577	Simulation and Model Checking for Close to Realtime Overtaking Planning	Fast and reliable trajectory planning is a key requirement of autonomous vehicles. In this paper we introduce a novel technique for planning the route of an autonomous vehicle on a straight rural road using the Spin model checker. We show how we can combine Spins ability to identify paths violating temporal properties ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	262,890
2007.09513	Feature-level Rating System using Customer Reviews and Review Votes	This work studies how we can obtain feature-level ratings of the mobile products from the customer reviews and review votes to influence decision making, both for new customers and manufacturers. Such a rating system gives a more comprehensive picture of the product than what a product-level rating system offers. While...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	187,973
2310.11877	The Curious Case of Hallucinatory (Un)answerability: Finding Truths in the Hidden States of Over-Confident Large Language Models	Large language models (LLMs) have been shown to possess impressive capabilities, while also raising crucial concerns about the faithfulness of their responses. A primary issue arising in this context is the management of (un)answerable queries by LLMs, which often results in hallucinatory behavior due to overconfidence...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	400,821
1908.07723	Improved Cardinality Estimation by Learning Queries Containment Rates	The containment rate of query Q1 in query Q2 over database D is the percentage of Q1's result tuples over D that are also in Q2's result over D. We directly estimate containment rates between pairs of queries over a specific database. For this, we use a specialized deep learning scheme, CRN, which is tailored to repres...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	142,355
2011.00395	A Framework of Combining Short-Term Spatial/Frequency Feature Extraction and Long-Term IndRNN for Activity Recognition	Smartphone sensors based human activity recognition is attracting increasing interests nowadays with the popularization of smartphones. With the high sampling rates of smartphone sensors, it is a highly long-range temporal recognition problem, especially with the large intra-class distances such as the smartphones carr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	204,193
1804.01568	Community structure detection and evaluation during the pre- and post-ictal hippocampal depth recordings	Detecting and evaluating regions of brain under various circumstances is one of the most interesting topics in computational neuroscience. However, the majority of the studies on detecting communities of a functional connectivity network of the brain is done on networks obtained from coherency attributes, and not from ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	94,245
2207.06964	Structure of Core-Periphery Communities	It has been experimentally shown that communities in social networks tend to have a core-periphery topology. However, there is still a limited understanding of the precise structure of core-periphery communities in social networks including the connectivity structure and interaction rates between agents. In this paper,...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	308,059
2408.01712	A General Ambiguity Model for Binary Edge Images with Edge Tracing and its Implementation	We present a general and intuitive ambiguity model for intersections, junctions and other structures in binary edge images. The model is combined with edge tracing, where edges are ordered sequences of connected pixels. The objective is to provide a versatile preprocessing method for tasks such as figure-ground segment...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	478,345
2308.04459	MCTS guided Genetic Algorithm for optimization of neural network weights	In this research, we investigate the possibility of applying a search strategy to genetic algorithms to explore the entire genetic tree structure. Several methods aid in performing tree searches; however, simpler algorithms such as breadth-first, depth-first, and iterative techniques are computation-heavy and often res...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	384,421
2412.16215	Zero-Shot Image Moderation in Google Ads with LLM-Assisted Textual Descriptions and Cross-modal Co-embeddings	We present a scalable and agile approach for ads image content moderation at Google, addressing the challenges of moderating massive volumes of ads with diverse content and evolving policies. The proposed method utilizes human-curated textual descriptions and cross-modal text-image co-embeddings to enable zero-shot cla...	false	false	false	false	true	true	false	false	false	false	false	true	false	false	false	false	false	false	519,418
2108.02694	Using Metamorphic Relations to Verify and Enhance Artcode Classification	Software testing is often hindered where it is impossible or impractical to determine the correctness of the behaviour or output of the software under test (SUT), a situation known as the oracle problem. An example of an area facing the oracle problem is automatic image classification, using machine learning to classif...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	249,413
2011.11201	Modular Action Concept Grounding in Semantic Video Prediction	Recent works in video prediction have mainly focused on passive forecasting and low-level action-conditional prediction, which sidesteps the learning of interaction between agents and objects. We introduce the task of semantic action-conditional video prediction, which uses semantic action labels to describe those inte...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	207,755
cs/0107012	Three-Stage Quantitative Neural Network Model of the Tip-of-the-Tongue Phenomenon	A new three-stage computer artificial neural network model of the tip-of-the-tongue phenomenon is shortly described, and its stochastic nature was demonstrated. A way to calculate strength and appearance probability of tip-of-the-tongue states, neural network mechanism of feeling-of-knowing phenomenon are proposed. The...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	537,384
1705.07768	Learning to Associate Words and Images Using a Large-scale Graph	We develop an approach for unsupervised learning of associations between co-occurring perceptual events using a large graph. We applied this approach to successfully solve the image captcha of China's railroad system. The approach is based on the principle of suspicious coincidence. In this particular problem, a user i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	73,887
1906.06090	Binary Classification using Pairs of Minimum Spanning Trees or N-ary Trees	One-class classifiers are trained with target class only samples. Intuitively, their conservative modelling of the class description may benefit classical classification tasks where classes are difficult to separate due to overlapping and data imbalance. In this work, three methods are proposed which leverage on the co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	135,212
2201.07737	COVID-19 impact on the international trade	Using the United Nations Comtrade database, we perform the Google matrix analysis of the multiproduct World Trade Network (WTN) for the years 2018-2020 comprising the emergence of the COVID-19 as a global pandemic. The applied algorithms -- the PageRank, the CheiRank and the reduced Google matrix -- take into account t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	276,119
1707.06142	Naive Bayes Classification for Subset Selection	This article focuses on the question of learning how to automatically select a subset of items among a bigger set. We introduce a methodology for the inference of ensembles of discrete values, based on the Naive Bayes assumption. Our motivation stems from practical use cases where one wishes to predict an unordered set...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	77,359
1502.01753	Monitoring Term Drift Based on Semantic Consistency in an Evolving Vector Field	Based on the Aristotelian concept of potentiality vs. actuality allowing for the study of energy and dynamics in language, we propose a field approach to lexical analysis. Falling back on the distributional hypothesis to statistically model word meaning, we used evolving fields as a metaphor to express time-dependent c...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	39,963
1608.01432	Decision Error Probability in a Two-stage Communication Network for Smart Grids with Imperfect Data Links	This paper analyzes a scenario where the distribution system operator needs to estimate whether the average power demand in a given period is above a predetermined threshold using an 1-bit memoryless scheme. Specifically, individual smart-meters periodically monitor the average power demand of their respective househol...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	59,429
2312.16476	SVGDreamer: Text Guided SVG Generation with Diffusion Model	Recently, text-guided scalable vector graphics (SVGs) synthesis has shown promise in domains such as iconography and sketch. However, existing text-to-SVG generation methods lack editability and struggle with visual quality and result diversity. To address these limitations, we propose a novel text-guided vector graphi...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	418,398
2112.06864	Frontiers in Collective Intelligence: A Workshop Report	In August of 2021, the Santa Fe Institute hosted a workshop on collective intelligence as part of its Foundations of Intelligence project. This project seeks to advance the field of artificial intelligence by promoting interdisciplinary research on the nature of intelligence. The workshop brought together computer scie...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	271,315
1809.03060	Active Inverse Reward Design	Designers of AI agents often iterate on the reward function in a trial-and-error process until they get the desired behavior, but this only guarantees good behavior in the training environment. We propose structuring this process as a series of queries asking the user to compare between different reward functions. Thus...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	107,221
2309.07618	Estimating mutual information for spike trains: a bird song example	Zebra finch are a model animal used in the study of audition. They are adept at recognizing zebra finch songs and the neural pathway involved in song recognition is well studied. Here, this example is used to illustrate the estimation of mutual information between stimulus and response using a Kozachenko-Leonenko estim...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	391,847
2212.10624	Random linear estimation with rotationally-invariant designs: Asymptotics at high temperature	We study estimation in the linear model $y=A\beta^\star+\epsilon$, in a Bayesian setting where $\beta^\star$ has an entrywise i.i.d. prior and the design $A$ is rotationally-invariant in law. In the large system limit as dimension and sample size increase proportionally, a set of related conjectures have been postulate...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	337,542
2004.14003	The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset	Purpose: To organize a knee MRI segmentation challenge for characterizing the semantic and clinical efficacy of automatic segmentation methods relevant for monitoring osteoarthritis progression. Methods: A dataset partition consisting of 3D knee MRI from 88 subjects at two timepoints with ground-truth articular (femo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	174,747
2303.01906	Generalized Semantic Segmentation by Self-Supervised Source Domain Projection and Multi-Level Contrastive Learning	Deep networks trained on the source domain show degraded performance when tested on unseen target domain data. To enhance the model's generalization ability, most existing domain generalization methods learn domain invariant features by suppressing domain sensitive features. Different from them, we propose a Domain Pro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	349,149
2102.13270	Single-angle Radon samples based reconstruction of functions in refinable shift-invariant space	The traditional approaches to computerized tomography (CT) depend on the samples of Radon transform at multiple angles. In optics, the real time imaging requires the reconstruction of an object by the samples of Radon transform at a single angle (SA). Driven by this and motivated by the connection between Bin Han's con...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	222,004
1903.04090	A Hybrid Framework for Action Recognition in Low-Quality Video Sequences	Vision-based activity recognition is essential for security, monitoring and surveillance applications. Further, real-time analysis having low-quality video and contain less information about surrounding due to poor illumination, and occlusions. Therefore, it needs a more robust and integrated model for low quality and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	123,896

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