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
1506.03350	GFDM Transceiver using Precoded Data and Low-complexity Multiplication in Time Domain	Future wireless communication systems are demanding a more flexible physical layer. GFDM is a block filtered multicarrier modulation scheme proposed to add multiple degrees of freedom and cover other waveforms in a single framework. In this paper, GFDM modulation and demodulation will be presented as a frequency-domain...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	44,036
2312.14303	Geo2SigMap: High-Fidelity RF Signal Mapping Using Geographic Databases	Radio frequency (RF) signal mapping, which is the process of analyzing and predicting the RF signal strength and distribution across specific areas, is crucial for cellular network planning and deployment. Traditional approaches to RF signal mapping rely on statistical models constructed based on measurement data, whic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	417,582
2412.03421	Governance as a complex, networked, democratic, satisfiability problem	Democratic governments comprise a subset of a population whose goal is to produce coherent decisions that solve societal challenges while respecting the will of the people they represent. New governance frameworks represent this problem as a social network rather than as a hierarchical pyramid with centralized authorit...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	513,953
2212.03296	Cheater's Bowl: Human vs. Computer Search Strategies for Open-Domain Question Answering	For humans and computers, the first step in answering an open-domain question is retrieving a set of relevant documents from a large corpus. However, the strategies that computers use fundamentally differ from those of humans. To better understand these differences, we design a gamified interface for data collection --...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	335,064
2405.20014	subMFL: Compatiple subModel Generation for Federated Learning in Device Heterogenous Environment	Federated Learning (FL) is commonly used in systems with distributed and heterogeneous devices with access to varying amounts of data and diverse computing and storage capacities. FL training process enables such devices to update the weights of a shared model locally using their local data and then a trusted central s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	459,158
1902.10402	Social Credibility Incorporating Semantic Analysis and Machine Learning: A Survey of the State-of-the-Art and Future Research Directions	The wealth of Social Big Data (SBD) represents a unique opportunity for organisations to obtain the excessive use of such data abundance to increase their revenues. Hence, there is an imperative need to capture, load, store, process, analyse, transform, interpret, and visualise such manifold social datasets to develop ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	122,672
2112.07844	Fix your Models by Fixing your Datasets	The quality of underlying training data is very crucial for building performant machine learning models with wider generalizabilty. However, current machine learning (ML) tools lack streamlined processes for improving the data quality. So, getting data quality insights and iteratively pruning the errors to obtain a dat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	271,604
2501.13598	A Transformer-based Autoregressive Decoder Architecture for Hierarchical Text Classification	Recent approaches in hierarchical text classification (HTC) rely on the capabilities of a pre-trained transformer model and exploit the label semantics and a graph encoder for the label hierarchy. In this paper, we introduce an effective hierarchical text classifier RADAr (Transformer-based Autoregressive Decoder Archi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	526,750
1511.07376	CNNdroid: GPU-Accelerated Execution of Trained Deep Convolutional Neural Networks on Android	Many mobile applications running on smartphones and wearable devices would potentially benefit from the accuracy and scalability of deep CNN-based machine learning algorithms. However, performance and energy consumption limitations make the execution of such computationally intensive algorithms on mobile devices prohib...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	49,420
2308.05445	Scheduling for Periodic Multi-Source Systems with Peak-Age Violation Guarantees	Age of information (AoI) is an effective performance metric measuring the freshness of information and is particularly suitable for applications involving status update. In this paper, using the age violation probability as the metric, scheduling for heterogeneous multi-source systems is studied. Two queueing disciplin...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	384,794
2106.11215	Machine Learning based optimization for interval uncertainty propagation	Two non-intrusive uncertainty propagation approaches are proposed for the performance analysis of engineering systems described by expensive-to-evaluate deterministic computer models with parameters defined as interval variables. These approaches employ a machine learning based optimization strategy, the so-called Baye...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	242,318
2106.07862	Domain Adaptive SiamRPN++ for Object Tracking in the Wild	Benefit from large-scale training data, recent advances in Siamese-based object tracking have achieved compelling results on the normal sequences. Whilst Siamese-based trackers assume training and test data follow an identical distribution. Suppose there is a set of foggy or rainy test sequences, it cannot be guarantee...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	241,084
2105.12685	Improved Quantum Codes from Metacirculant Graphs via Self-Dual Additive $\mathbb{F}_4$-Codes	We use symplectic self-dual additive codes over $\mathbb{F}_4$ obtained from metacirculant graphs to construct, for the first time, $[[\ell, 0, d ]]$ qubit codes with parameters $(\ell,d) \in \{(78, 20), (90, 21), (91, 22), (93,21),(96,21)\}$. Secondary constructions applied to the qubit codes result in many qubit code...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	237,069
2010.13399	Optimal Binary LCD Codes	Linear complementary dual codes (or codes with complementary duals) are codes whose intersections with their dual codes are trivial. These codes were first introduced by Massey in 1964. Nowadays, LCD codes are extensively studied in the literature and widely applied in data storage, cryptography, etc. In this paper, we...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	203,117
1609.08470	A computer program for simulating time travel and a possible 'solution' for the grandfather paradox	While the possibility of time travel in physics is still debated, the explosive growth of virtual-reality simulations opens up new possibilities to rigorously explore such time travel and its consequences in the digital domain. Here we provide a computational model of time travel and a computer program that allows expl...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	61,602
2307.08053	The Extended Codes of Some Linear Codes	The classical way of extending an $[n, k, d]$ linear code $\C$ is to add an overall parity-check coordinate to each codeword of the linear code $\C$. This extended code, denoted by $\overline{\C}(-\bone)$ and called the standardly extended code of $\C$, is a linear code with parameters $[n+1, k, \bar{d}]$, where $\bar{...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	379,653
2101.12236	Beyond Capacity: The Joint Time-Rate Region	The traditional notion of capacity studied in the context of memoryless network communication builds on the concept of block-codes and requires that, for sufficiently large blocklength n, all receiver nodes simultaneously decode their required information after n channel uses. In this work, we generalize the traditiona...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	217,516
2411.08911	A Message Passing Neural Network Surrogate Model for Bond-Associated Peridynamic Material Correspondence Formulation	Peridynamics is a non-local continuum mechanics theory that offers unique advantages for modeling problems involving discontinuities and complex deformations. Within the peridynamic framework, various formulations exist, among which the material correspondence formulation stands out for its ability to directly incorpor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	508,069
1904.10578	When and where do you want to hide? Recommendation of location privacy preferences with local differential privacy	In recent years, it has become easy to obtain location information quite precisely. However, the acquisition of such information has risks such as individual identification and leakage of sensitive information, so it is necessary to protect the privacy of location information. For this purpose, people should know their...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	128,652
2210.03692	Compressing Video Calls using Synthetic Talking Heads	We leverage the modern advancements in talking head generation to propose an end-to-end system for talking head video compression. Our algorithm transmits pivot frames intermittently while the rest of the talking head video is generated by animating them. We use a state-of-the-art face reenactment network to detect key...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	322,137
2105.03014	BasisNet: Two-stage Model Synthesis for Efficient Inference	In this work, we present BasisNet which combines recent advancements in efficient neural network architectures, conditional computation, and early termination in a simple new form. Our approach incorporates a lightweight model to preview the input and generate input-dependent combination coefficients, which later contr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	234,000
1902.01109	Strategies for Structuring Story Generation	Writers generally rely on plans or sketches to write long stories, but most current language models generate word by word from left to right. We explore coarse-to-fine models for creating narrative texts of several hundred words, and introduce new models which decompose stories by abstracting over actions and entities....	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	120,592
2101.09884	Domain-Dependent Speaker Diarization for the Third DIHARD Challenge	This report presents the system developed by the ABSP Laboratory team for the third DIHARD speech diarization challenge. Our main contribution in this work is to develop a simple and efficient solution for acoustic domain dependent speech diarization. We explore speaker embeddings for \emph{acoustic domain identificati...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	216,750
2402.17078	Batch Estimation of a Steady, Uniform, Flow-Field from Ground Velocity and Heading Measurements	This paper presents three batch estimation methods that use noisy ground velocity and heading measurements from a vehicle executing a circular orbit (or similar large heading change maneuver) to estimate the speed and direction of a steady, uniform, flow-field. The methods are based on a simple kinematic model of the v...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	432,829
1509.06019	LT Codes Combined with Network Coding for Multihop Powerline Smart Grid Networks	This paper describes a novel approach for combining Luby Transform (LT) codes and Network Coding (NC) in the context of PowerLine Communications (PLC) smart grid networks. Multihop transmissions of LT-encoded data on PLC networks are considered and algorithms to combine data at relay nodes are proposed. Without the nee...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	47,111
2106.00771	SWIPT with Intelligent Reflecting Surfaces under Spatial Correlation	Intelligent reflecting surfaces (IRSs) can be beneficial to both information and energy transfer, due to the gains achieved by their multiple elements. In this work, we deal with the impact of spatial correlation between the IRS elements, in the context of simultaneous wireless information and power transfer. The perfo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	238,245
1807.03089	Video Summarisation by Classification with Deep Reinforcement Learning	Most existing video summarisation methods are based on either supervised or unsupervised learning. In this paper, we propose a reinforcement learning-based weakly supervised method that exploits easy-to-obtain, video-level category labels and encourages summaries to contain category-related information and maintain cat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	102,421
2111.11242	Prediction of Probabilistic Transient Stability Using Support Vector Machine	Transient stability assessment is an integral part of dynamic security assessment of power systems. Traditional methods of transient stability assessment, such as time domain simulation approach and direct methods, are appropriate for offline studies and thus, cannot be applied for online transient stability prediction...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	267,598
2203.00512	A Deep Bayesian Neural Network for Cardiac Arrhythmia Classification with Rejection from ECG Recordings	With the development of deep learning-based methods, automated classification of electrocardiograms (ECGs) has recently gained much attention. Although the effectiveness of deep neural networks has been encouraging, the lack of information given by the outputs restricts clinicians' reexamination. If the uncertainty est...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	283,028
2002.10110	Revisiting EXTRA for Smooth Distributed Optimization	EXTRA is a popular method for dencentralized distributed optimization and has broad applications. This paper revisits EXTRA. First, we give a sharp complexity analysis for EXTRA with the improved $O\left(\left(\frac{L}{\mu}+\frac{1}{1-\sigma_2(W)}\right)\log\frac{1}{\epsilon(1-\sigma_2(W))}\right)$ communication and co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	165,289
2212.01661	Unsupervised Fine-Tuning Data Selection for ASR Using Self-Supervised Speech Models	Self-supervised learning (SSL) has been able to leverage unlabeled data to boost the performance of automatic speech recognition (ASR) models when we have access to only a small amount of transcribed speech data. However, this raises the question of which subset of the available unlabeled data should be selected for tr...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	334,517
2006.01169	RNNs on Monitoring Physical Activity Energy Expenditure in Older People	Through the quantification of physical activity energy expenditure (PAEE), health care monitoring has the potential to stimulate vital and healthy ageing, inducing behavioural changes in older people and linking these to personal health gains. To be able to measure PAEE in a monitoring environment, methods from wearabl...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	179,689
2410.17135	Reinforcement Learning for Data-Driven Workflows in Radio Interferometry. I. Principal Demonstration in Calibration	Radio interferometry is an observational technique used to study astrophysical phenomena. Data gathered by an interferometer requires substantial processing before astronomers can extract the scientific information from it. Data processing consists of a sequence of calibration and analysis procedures where choices must...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	501,323
1905.12126	Using Ontologies To Improve Performance In Massively Multi-label Prediction Models	Massively multi-label prediction/classification problems arise in environments like health-care or biology where very precise predictions are useful. One challenge with massively multi-label problems is that there is often a long-tailed frequency distribution for the labels, which results in few positive examples for t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	132,659
2106.13031	Towards Biologically Plausible Convolutional Networks	Convolutional networks are ubiquitous in deep learning. They are particularly useful for images, as they reduce the number of parameters, reduce training time, and increase accuracy. However, as a model of the brain they are seriously problematic, since they require weight sharing - something real neurons simply cannot...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	242,934
1804.04548	Unique Reconstruction of Coded Strings from Multiset Substring Spectra	The problem of reconstructing strings from their substring spectra has a long history and in its most simple incarnation asks for determining under which conditions the spectrum uniquely determines the string. We study the problem of coded string reconstruction from multiset substring spectra, where the strings are res...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	94,881
2405.17984	Cross-Context Backdoor Attacks against Graph Prompt Learning	Graph Prompt Learning (GPL) bridges significant disparities between pretraining and downstream applications to alleviate the knowledge transfer bottleneck in real-world graph learning. While GPL offers superior effectiveness in graph knowledge transfer and computational efficiency, the security risks posed by backdoor ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	458,222
2302.07608	Uncertainty-Estimation with Normalized Logits for Out-of-Distribution Detection	Out-of-distribution (OOD) detection is critical for preventing deep learning models from making incorrect predictions to ensure the safety of artificial intelligence systems. Especially in safety-critical applications such as medical diagnosis and autonomous driving, the cost of incorrect decisions is usually unbearabl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	345,783
2303.04635	Diffusing Gaussian Mixtures for Generating Categorical Data	Learning a categorical distribution comes with its own set of challenges. A successful approach taken by state-of-the-art works is to cast the problem in a continuous domain to take advantage of the impressive performance of the generative models for continuous data. Amongst them are the recently emerging diffusion pro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	350,164
2204.12679	Document-Level Relation Extraction with Sentences Importance Estimation and Focusing	Document-level relation extraction (DocRE) aims to determine the relation between two entities from a document of multiple sentences. Recent studies typically represent the entire document by sequence- or graph-based models to predict the relations of all entity pairs. However, we find that such a model is not robust a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	293,561
2004.06947	Benchmarking Unsupervised Outlier Detection with Realistic Synthetic Data	Benchmarking unsupervised outlier detection is difficult. Outliers are rare, and existing benchmark data contains outliers with various and unknown characteristics. Fully synthetic data usually consists of outliers and regular instance with clear characteristics and thus allows for a more meaningful evaluation of detec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	172,646
2409.08706	L3Cube-IndicQuest: A Benchmark Question Answering Dataset for Evaluating Knowledge of LLMs in Indic Context	Large Language Models (LLMs) have made significant progress in incorporating Indic languages within multilingual models. However, it is crucial to quantitatively assess whether these languages perform comparably to globally dominant ones, such as English. Currently, there is a lack of benchmark datasets specifically de...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	488,029
2304.06019	Generating Aligned Pseudo-Supervision from Non-Aligned Data for Image Restoration in Under-Display Camera	Due to the difficulty in collecting large-scale and perfectly aligned paired training data for Under-Display Camera (UDC) image restoration, previous methods resort to monitor-based image systems or simulation-based methods, sacrificing the realness of the data and introducing domain gaps. In this work, we revisit the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	357,820
2409.12045	Handling Long-Term Safety and Uncertainty in Safe Reinforcement Learning	Safety is one of the key issues preventing the deployment of reinforcement learning techniques in real-world robots. While most approaches in the Safe Reinforcement Learning area do not require prior knowledge of constraints and robot kinematics and rely solely on data, it is often difficult to deploy them in complex r...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	489,415
2404.01116	Intelligent Robotic Control System Based on Computer Vision Technology	The article explores the intersection of computer vision technology and robotic control, highlighting its importance in various fields such as industrial automation, healthcare, and environmental protection. Computer vision technology, which simulates human visual observation, plays a crucial role in enabling robots to...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	443,258
2111.06714	A Review on Communication Protocols for Autonomous Unmanned Aerial Vehicles for Inspection Application	The communication system is a critical part of the system design for the autonomous UAV. It has to address different considerations, including efficiency, reliability and mobility of the UAV. In addition, a multi-UAV system requires a communication system to assist information sharing, task allocation and collaboration...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	266,150
2202.07414	Interpretable Reinforcement Learning with Multilevel Subgoal Discovery	We propose a novel Reinforcement Learning model for discrete environments, which is inherently interpretable and supports the discovery of deep subgoal hierarchies. In the model, an agent learns information about environment in the form of probabilistic rules, while policies for (sub)goals are learned as combinations t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	280,539
1811.02722	Scalable Bottom-up Subspace Clustering using FP-Trees for High Dimensional Data	Subspace clustering aims to find groups of similar objects (clusters) that exist in lower dimensional subspaces from a high dimensional dataset. It has a wide range of applications, such as analysing high dimensional sensor data or DNA sequences. However, existing algorithms have limitations in finding clusters in non-...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,669
0901.0042	A family of asymptotically good quantum codes based on code concatenation	We explicitly construct an infinite family of asymptotically good concatenated quantum stabilizer codes where the outer code uses CSS-type quantum Reed-Solomon code and the inner code uses a set of special quantum codes. In the field of quantum error-correcting codes, this is the first time that a family of asymptotica...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,866
cs/0503012	First-order Complete and Computationally Complete Query Languages for Spatio-Temporal Databases	We address a fundamental question concerning spatio-temporal database systems: ``What are exactly spatio-temporal queries?'' We define spatio-temporal queries to be computable mappings that are also generic, meaning that the result of a query may only depend to a limited extent on the actual internal representation of ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	538,587
2103.14321	Online Learning Koopman operator for closed-loop electrical neurostimulation in epilepsy	Electrical neuromodulation as a palliative treatment has been increasingly used in the control of epilepsy. However, current neuromodulations commonly implement predetermined actuation strategies and lack the capability of self-adaptively adjusting stimulation inputs. In this work, rooted in optimal control theory, we ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	226,817
2412.14916	From Point to probabilistic gradient boosting for claim frequency and severity prediction	Gradient boosting for decision tree algorithms are increasingly used in actuarial applications as they show superior predictive performance over traditional generalized linear models. Many improvements and sophistications to the first gradient boosting machine algorithm exist. We present in a unified notation, and cont...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	518,895
2311.14652	One Pass Streaming Algorithm for Super Long Token Attention Approximation in Sublinear Space	Attention computation takes both the time complexity of $O(n^2)$ and the space complexity of $O(n^2)$ simultaneously, which makes deploying Large Language Models (LLMs) in streaming applications that involve long contexts requiring substantial computational resources. In recent OpenAI DevDay (Nov 6, 2023), OpenAI relea...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	410,184
2312.04060	Differentiable Registration of Images and LiDAR Point Clouds with VoxelPoint-to-Pixel Matching	Cross-modality registration between 2D images from cameras and 3D point clouds from LiDARs is a crucial task in computer vision and robotic. Previous methods estimate 2D-3D correspondences by matching point and pixel patterns learned by neural networks, and use Perspective-n-Points (PnP) to estimate rigid transformatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	413,532
2411.00630	STAA: Spatio-Temporal Attention Attribution for Real-Time Interpreting Transformer-based Video Models	Transformer-based models have achieved state-of-the-art performance in various computer vision tasks, including image and video analysis. However, Transformer's complex architecture and black-box nature pose challenges for explainability, a crucial aspect for real-world applications and scientific inquiry. Current Expl...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	504,677
2402.03904	Deep Frequency-Aware Functional Maps for Robust Shape Matching	Deep functional map frameworks are widely employed for 3D shape matching. However, most existing deep functional map methods cannot adaptively capture important frequency information for functional map estimation in specific matching scenarios, i.e., lacking \textit{frequency awareness}, resulting in poor performance w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	427,244
2106.15432	On exploring the potential of quantum auto-encoder for learning quantum systems	The frequent interactions between quantum computing and machine learning revolutionize both fields. One prototypical achievement is the quantum auto-encoder (QAE), as the leading strategy to relieve the curse of dimensionality ubiquitous in the quantum world. Despite its attractive capabilities, practical applications ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	243,767
2409.17497	Precise Interception Flight Targets by Image-based Visual Servoing of Multicopter	Interception of low-altitude intruding targets with low-cost drones equipped strapdown camera presents a competitive option. However, the malicious maneuvers by the non-cooperative target and the coupling of the camera make the task challenging. To solve this problem, an Image-Based Visual Servoing (IBVS) control algor...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	491,830
2404.13645	PEACH: Pretrained-embedding Explanation Across Contextual and Hierarchical Structure	In this work, we propose a novel tree-based explanation technique, PEACH (Pretrained-embedding Explanation Across Contextual and Hierarchical Structure), that can explain how text-based documents are classified by using any pretrained contextual embeddings in a tree-based human-interpretable manner. Note that PEACH can...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	448,377
1906.06637	A Closer Look at Double Backpropagation	In recent years, an increasing number of neural network models have included derivatives with respect to inputs in their loss functions, resulting in so-called double backpropagation for first-order optimization. However, so far no general description of the involved derivatives exists. Here, we cover a wide array of s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	135,370
2205.05398	Scalable Stochastic Parametric Verification with Stochastic Variational Smoothed Model Checking	Parametric verification of linear temporal properties for stochastic models can be expressed as computing the satisfaction probability of a certain property as a function of the parameters of the model. Smoothed model checking (smMC) aims at inferring the satisfaction function over the entire parameter space from a lim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	295,920
1907.05638	Learning Functions over Sets via Permutation Adversarial Networks	In this paper, we consider the problem of learning functions over sets, i.e., functions that are invariant to permutations of input set items. Recent approaches of pooling individual element embeddings can necessitate extremely large embedding sizes for challenging functions. We address this challenge by allowing stand...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	138,419
1908.04347	Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance	In recent years there has been a growing interest in image generation through deep learning. While an important part of the evaluation of the generated images usually involves visual inspection, the inclusion of human perception as a factor in the training process is often overlooked. In this paper we propose an altern...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	141,449
2404.17205	Two in One Go: Single-stage Emotion Recognition with Decoupled Subject-context Transformer	Emotion recognition aims to discern the emotional state of subjects within an image, relying on subject-centric and contextual visual cues. Current approaches typically follow a two-stage pipeline: first localize subjects by off-the-shelf detectors, then perform emotion classification through the late fusion of subject...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	449,777
2011.07230	TDAsweep: A Novel Dimensionality Reduction Method for Image Classification Tasks	One of the most celebrated achievements of modern machine learning technology is automatic classification of images. However, success is typically achieved only with major computational costs. Here we introduce TDAsweep, a machine learning tool aimed at improving the efficiency of automatic classification of images.	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	206,486
2411.08733	Dynamic Rewarding with Prompt Optimization Enables Tuning-free Self-Alignment of Language Models	Aligning Large Language Models (LLMs) traditionally relies on costly training and human preference annotations. Self-alignment seeks to reduce these expenses by enabling models to align themselves. To further lower costs and achieve alignment without any expensive tuning or annotations, we introduce a new tuning-free a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	507,994
cs/9809022	Modelling Users, Intentions, and Structure in Spoken Dialog	We outline how utterances in dialogs can be interpreted using a partial first order logic. We exploit the capability of this logic to talk about the truth status of formulae to define a notion of coherence between utterances and explain how this coherence relation can serve for the construction of AND/OR trees that rep...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	540,394
2308.09593	Investigation of Architectures and Receptive Fields for Appearance-based Gaze Estimation	With the rapid development of deep learning technology in the past decade, appearance-based gaze estimation has attracted great attention from both computer vision and human-computer interaction research communities. Fascinating methods were proposed with variant mechanisms including soft attention, hard attention, two...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	386,350
2304.04455	Bayesian optimization for sparse neural networks with trainable activation functions	In the literature on deep neural networks, there is considerable interest in developing activation functions that can enhance neural network performance. In recent years, there has been renewed scientific interest in proposing activation functions that can be trained throughout the learning process, as they appear to i...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	357,226
2205.10139	Towards efficient feature sharing in MIMO architectures	Multi-input multi-output architectures propose to train multiple subnetworks within one base network and then average the subnetwork predictions to benefit from ensembling for free. Despite some relative success, these architectures are wasteful in their use of parameters. Indeed, we highlight in this paper that the le...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	297,584
2202.01211	An Adaptive Deep Clustering Pipeline to Inform Text Labeling at Scale	Mining the latent intentions from large volumes of natural language inputs is a key step to help data analysts design and refine Intelligent Virtual Assistants (IVAs) for customer service and sales support. We created a flexible and scalable clustering pipeline within the Verint Intent Manager (VIM) that integrates the...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	278,404
2406.18229	Advancing Robotic Surgery: Affordable Kinesthetic and Tactile Feedback Solutions for Endotrainers	The proliferation of robot-assisted minimally invasive surgery highlights the need for advanced training tools such as cost-effective robotic endotrainers. Current surgical robots often lack haptic feedback, which is crucial for providing surgeons with a real-time sense of touch. This absence can impact the surgeon's a...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	467,927
2401.16181	On Decentralized Linearly Separable Computation With the Minimum Computation Cost	The distributed linearly separable computation problem finds extensive applications across domains such as distributed gradient coding, distributed linear transform, real-time rendering, etc. In this paper, we investigate this problem in a fully decentralized scenario, where $\mathsf{N}$ workers collaboratively perform...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	424,724
1307.4689	DASH: Dynamic Approach for Switching Heuristics	Complete tree search is a highly effective method for tackling MIP problems, and over the years, a plethora of branching heuristics have been introduced to further refine the technique for varying problems. Recently, portfolio algorithms have taken the process a step further, trying to predict the best heuristic for ea...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	25,901
1807.11537	Estimating Failure in Brittle Materials using Graph Theory	In brittle fracture applications, failure paths, regions where the failure occurs and damage statistics, are some of the key quantities of interest (QoI). High-fidelity models for brittle failure that accurately predict these QoI exist but are highly computationally intensive, making them infeasible to incorporate in u...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	104,188
2404.04578	GLCM-Based Feature Combination for Extraction Model Optimization in Object Detection Using Machine Learning	In the era of modern technology, object detection using the Gray Level Co-occurrence Matrix (GLCM) extraction method plays a crucial role in object recognition processes. It finds applications in real-time scenarios such as security surveillance and autonomous vehicle navigation, among others. Computational efficiency ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,709
2111.14843	Catch Me If You Hear Me: Audio-Visual Navigation in Complex Unmapped Environments with Moving Sounds	Audio-visual navigation combines sight and hearing to navigate to a sound-emitting source in an unmapped environment. While recent approaches have demonstrated the benefits of audio input to detect and find the goal, they focus on clean and static sound sources and struggle to generalize to unheard sounds. In this work...	false	false	true	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	268,733
1201.2478	Global stabilization of nonlinear systems based on vector control lyapunov functions	This paper studies the use of vector Lyapunov functions for the design of globally stabilizing feedback laws for nonlinear systems. Recent results on vector Lyapunov functions are utilized. The main result of the paper shows that the existence of a vector control Lyapunov function is a necessary and sufficient conditio...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	13,780
1707.06988	A Framework for Multi-Vehicle Navigation Using Feedback-Based Motion Primitives	We present a hybrid control framework for solving a motion planning problem among a collection of heterogenous agents. The proposed approach utilizes a finite set of low-level motion primitives, each based on a piecewise affine feedback control, to generate complex motions in a gridded workspace. The constraints on all...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	77,525
2401.10710	Classification with neural networks with quadratic decision functions	Neural networks with quadratic decision functions have been introduced as alternatives to standard neural networks with affine linear ones. They are advantageous when the objects or classes to be identified are compact and of basic geometries like circles, ellipses etc. In this paper we investigate the use of such ansa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	422,739
1810.11726	Towards Robust Deep Neural Networks	We investigate the topics of sensitivity and robustness in feedforward and convolutional neural networks. Combining energy landscape techniques developed in computational chemistry with tools drawn from formal methods, we produce empirical evidence indicating that networks corresponding to lower-lying minima in the opt...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	111,576
2001.03133	A Generalization of Teo and Sethuraman's Median Stable Marriage Theorem	Let $L$ be any finite distributive lattice and $B$ be any boolean predicate defined on $L$ such that the set of elements satisfying $B$ is a sublattice of $L$. Consider any subset $M$ of $L$ of size $k$ of elements of $L$ that satisfy $B$. Then, we show that $k$ generalized median elements generated from $M$ also satis...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	159,892
2203.09200	Novel Consistency Check For Fast Recursive Reconstruction Of Non-Regularly Sampled Video Data	Quarter sampling is a novel sensor design that allows for an acquisition of higher resolution images without increasing the number of pixels. When being used for video data, one out of four pixels is measured in each frame. Effectively, this leads to a non-regular spatio-temporal sub-sampling. Compared to purely spatia...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,073
1910.13584	A Tunably Compliant Origami Mechanism for Dynamically Dexterous Robots	We present an approach to overcoming challenges in dynamical dexterity for robots through tunable origami structures. Our work leverages a one-parameter family of flat sheet crease patterns that folds into origami bellows, whose axial compliance can be tuned to select desired stiffness. Concentrically arranged cylinder...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	151,426
2111.09098	Unifying Heterogeneous Electronic Health Records Systems via Text-Based Code Embedding	EHR systems lack a unified code system forrepresenting medical concepts, which acts asa barrier for the deployment of deep learningmodels in large scale to multiple clinics and hos-pitals. To overcome this problem, we introduceDescription-based Embedding,DescEmb, a code-agnostic representation learning framework forEHR...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	266,909
2410.16324	CybORG++: An Enhanced Gym for the Development of Autonomous Cyber Agents	CybORG++ is an advanced toolkit for reinforcement learning research focused on network defence. Building on the CAGE 2 CybORG environment, it introduces key improvements, including enhanced debugging capabilities, refined agent implementation support, and a streamlined environment that enables faster training and easie...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	500,981
2502.03652	The Cost of Shuffling in Private Gradient Based Optimization	We consider the problem of differentially private (DP) convex empirical risk minimization (ERM). While the standard DP-SGD algorithm is theoretically well-established, practical implementations often rely on shuffled gradient methods that traverse the training data sequentially rather than sampling with replacement in ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	530,799
1903.07319	What You Say and How You Say it: Joint Modeling of Topics and Discourse in Microblog Conversations	This paper presents an unsupervised framework for jointly modeling topic content and discourse behavior in microblog conversations. Concretely, we propose a neural model to discover word clusters indicating what a conversation concerns (i.e., topics) and those reflecting how participants voice their opinions (i.e., dis...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	124,591
2105.10360	Multi-source Learning via Completion of Block-wise Overlapping Noisy Matrices	Matrix completion has attracted attention in many fields, including statistics, applied mathematics, and electrical engineering. Most of the works focus on the independent sampling models under which the observed entries are sampled independently. Motivated by applications in the integration of knowledge graphs derived...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	236,371
2301.05620	Optimizing Facial Expressions of an Android Robot Effectively: a Bayesian Optimization Approach	Expressing various facial emotions is an important social ability for efficient communication between humans. A key challenge in human-robot interaction research is providing androids with the ability to make various human-like facial expressions for efficient communication with humans. The android Nikola, we have deve...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	340,401
2202.08552	EBHI:A New Enteroscope Biopsy Histopathological H&E Image Dataset for Image Classification Evaluation	Background and purpose: Colorectal cancer has become the third most common cancer worldwide, accounting for approximately 10% of cancer patients. Early detection of the disease is important for the treatment of colorectal cancer patients. Histopathological examination is the gold standard for screening colorectal cance...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	280,926
2111.13978	Deep Q-Learning based Reinforcement Learning Approach for Network Intrusion Detection	The rise of the new generation of cyber threats demands more sophisticated and intelligent cyber defense solutions equipped with autonomous agents capable of learning to make decisions without the knowledge of human experts. Several reinforcement learning methods (e.g., Markov) for automated network intrusion tasks hav...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	268,449
2301.10028	Super forecasting the technological singularity risks from artificial intelligence	The article forecasts emerging cyber-risks from the integration of AI in cybersecurity.	false	false	false	false	true	false	false	false	false	false	false	false	true	true	false	false	false	false	341,678
2201.12799	Recognition of Implicit Geographic Movement in Text	Analyzing the geographic movement of humans, animals, and other phenomena is a growing field of research. This research has benefited urban planning, logistics, animal migration understanding, and much more. Typically, the movement is captured as precise geographic coordinates and time stamps with Global Positioning Sy...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	277,785
2008.10351	Model Generalization in Deep Learning Applications for Land Cover Mapping	Recent work has shown that deep learning models can be used to classify land-use data from geospatial satellite imagery. We show that when these deep learning models are trained on data from specific continents/seasons, there is a high degree of variability in model performance on out-of-sample continents/seasons. This...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	192,971
2006.03951	Contextual Bandits with Side-Observations	We investigate contextual bandits in the presence of side-observations across arms in order to design recommendation algorithms for users connected via social networks. Users in social networks respond to their friends' activity, and hence provide information about each other's preferences. In our model, when a learnin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	180,494
1811.07468	Multi-scale 3D Convolution Network for Video Based Person Re-Identification	This paper proposes a two-stream convolution network to extract spatial and temporal cues for video based person Re-Identification (ReID). A temporal stream in this network is constructed by inserting several Multi-scale 3D (M3D) convolution layers into a 2D CNN network. The resulting M3D convolution network introduces...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	113,776
2102.02038	Isometric Propagation Network for Generalized Zero-shot Learning	Zero-shot learning (ZSL) aims to classify images of an unseen class only based on a few attributes describing that class but no access to any training sample. A popular strategy is to learn a mapping between the semantic space of class attributes and the visual space of images based on the seen classes and their data. ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	218,306
1809.04280	Safe Navigation with Human Instructions in Complex Scenes	In this paper, we present a robotic navigation algorithm with natural language interfaces, which enables a robot to safely walk through a changing environment with moving persons by following human instructions such as "go to the restaurant and keep away from people". We first classify human instructions into three typ...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	107,524
2211.11944	COVID-Net Assistant: A Deep Learning-Driven Virtual Assistant for COVID-19 Symptom Prediction and Recommendation	As the COVID-19 pandemic continues to put a significant burden on healthcare systems worldwide, there has been growing interest in finding inexpensive symptom pre-screening and recommendation methods to assist in efficiently using available medical resources such as PCR tests. In this study, we introduce the design of ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,927

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