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
2310.14664	Data Pruning via Moving-one-Sample-out	In this paper, we propose a novel data-pruning approach called moving-one-sample-out (MoSo), which aims to identify and remove the least informative samples from the training set. The core insight behind MoSo is to determine the importance of each sample by assessing its impact on the optimal empirical risk. This is ac...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	401,964
2101.01142	Advanced Machine Learning Techniques for Fake News (Online Disinformation) Detection: A Systematic Mapping Study	Fake news has now grown into a big problem for societies and also a major challenge for people fighting disinformation. This phenomenon plagues democratic elections, reputations of individual persons or organizations, and has negatively impacted citizens, (e.g., during the COVID-19 pandemic in the US or Brazil). Hence,...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	214,294
1908.05287	Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems	Aggregating multiple learners through an ensemble of models aim to make better predictions by capturing the underlying distribution of the data more accurately. Different ensembling methods, such as bagging, boosting, and stacking/blending, have been studied and adopted extensively in research and practice. While baggi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	141,680
2303.12023	Logical Reasoning over Natural Language as Knowledge Representation: A Survey	Logical reasoning is central to human cognition and intelligence. It includes deductive, inductive, and abductive reasoning. Past research of logical reasoning within AI uses formal language as knowledge representation and symbolic reasoners. However, reasoning with formal language has proved challenging (e.g., brittle...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	353,106
2301.08654	Automated extraction of capacitive coupling for quantum dot systems	Gate-defined quantum dots (QDs) have appealing attributes as a quantum computing platform. However, near-term devices possess a range of possible imperfections that need to be accounted for during the tuning and operation of QD devices. One such problem is the capacitive cross-talk between the metallic gates that defin...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	341,251
2410.05261	TextHawk2: A Large Vision-Language Model Excels in Bilingual OCR and Grounding with 16x Fewer Tokens	Reading dense text and locating objects within images are fundamental abilities for Large Vision-Language Models (LVLMs) tasked with advanced jobs. Previous LVLMs, including superior proprietary models like GPT-4o, have struggled to excel in both tasks simultaneously. Moreover, previous LVLMs with fine-grained percepti...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	495,638
1402.1670	Hierarchical organization versus self-organization	In this paper we try to define the difference between hierarchical organization and self-organization. Organization is defined as a structure with a function. So we can define the difference between hierarchical organization and self-organization both on the structure as on the function. In the next two chapters these ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	30,694
2403.10923	Interpretable Machine Learning for TabPFN	The recently developed Prior-Data Fitted Networks (PFNs) have shown very promising results for applications in low-data regimes. The TabPFN model, a special case of PFNs for tabular data, is able to achieve state-of-the-art performance on a variety of classification tasks while producing posterior predictive distributi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	438,427
2006.13400	Wikipedia and Westminster: Quality and Dynamics of Wikipedia Pages about UK Politicians	Wikipedia is a major source of information providing a large variety of content online, trusted by readers from around the world. Readers go to Wikipedia to get reliable information about different subjects, one of the most popular being living people, and especially politicians. While a lot is known about the general ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	183,896
2306.00526	Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering	Layout-aware pre-trained models has achieved significant progress on document image question answering. They introduce extra learnable modules into existing language models to capture layout information within document images from text bounding box coordinates obtained by OCR tools. However, extra modules necessitate p...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	370,045
2204.06822	Stream-based Active Learning with Verification Latency in Non-stationary Environments	Data stream classification is an important problem in the field of machine learning. Due to the non-stationary nature of the data where the underlying distribution changes over time (concept drift), the model needs to continuously adapt to new data statistics. Stream-based Active Learning (AL) approaches address this p...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	291,458
1304.3449	Statistical Mechanics Algorithm for Response to Targets (SMART)	It is proposed to apply modern methods of nonlinear nonequilibrium statistical mechanics to develop software algorithms that will optimally respond to targets within short response times with minimal computer resources. This Statistical Mechanics Algorithm for Response to Targets (SMART) can be developed with a view to...	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,888
2303.02508	Chasing Low-Carbon Electricity for Practical and Sustainable DNN Training	Deep learning has experienced significant growth in recent years, resulting in increased energy consumption and carbon emission from the use of GPUs for training deep neural networks (DNNs). Answering the call for sustainability, conventional solutions have attempted to move training jobs to locations or time frames wi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	349,388
2110.08713	Pareto Navigation Gradient Descent: a First-Order Algorithm for Optimization in Pareto Set	Many modern machine learning applications, such as multi-task learning, require finding optimal model parameters to trade-off multiple objective functions that may conflict with each other. The notion of the Pareto set allows us to focus on the set of (often infinite number of) models that cannot be strictly improved. ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	261,523
1507.03934	Recurrent Polynomial Network for Dialogue State Tracking	Dialogue state tracking (DST) is a process to estimate the distribution of the dialogue states as a dialogue progresses. Recent studies on constrained Markov Bayesian polynomial (CMBP) framework take the first step towards bridging the gap between rule-based and statistical approaches for DST. In this paper, the gap is...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	45,119
1709.00744	An Improved Algorithm for E-Generalization	E-generalization computes common generalizations of given ground terms w.r.t. a given equational background theory E. In 2005 [arXiv:1403.8118], we had presented a computation approach based on standard regular tree grammar algorithms, and a Prolog prototype implementation. In this report, we present algorithmic improv...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	79,965
2303.08757	CT Perfusion is All We Need: 4D CNN Segmentation of Penumbra and Core in Patients With Suspected Ischemic Stroke	Precise and fast prediction methods for ischemic areas comprised of dead tissue, core, and salvageable tissue, penumbra, in acute ischemic stroke (AIS) patients are of significant clinical interest. They play an essential role in improving diagnosis and treatment planning. Computed Tomography (CT) scan is one of the pr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	351,766
1711.03987	Optimised Maintenance of Datalog Materialisations	To efficiently answer queries, datalog systems often materialise all consequences of a datalog program, so the materialisation must be updated whenever the input facts change. Several solutions to the materialisation update problem have been proposed. The Delete/Rederive (DRed) and the Backward/Forward (B/F) algorithms...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	84,306
2211.01346	Predictive Crypto-Asset Automated Market Making Architecture for Decentralized Finance using Deep Reinforcement Learning	The study proposes a quote-driven predictive automated market maker (AMM) platform with on-chain custody and settlement functions, alongside off-chain predictive reinforcement learning capabilities to improve liquidity provision of real-world AMMs. The proposed AMM architecture is an augmentation to the Uniswap V3, a c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	328,198
2407.11644	Perception Helps Planning: Facilitating Multi-Stage Lane-Level Integration via Double-Edge Structures	When planning for autonomous driving, it is crucial to consider essential traffic elements such as lanes, intersections, traffic regulations, and dynamic agents. However, they are often overlooked by the traditional end-to-end planning methods, likely leading to inefficiencies and non-compliance with traffic regulation...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	473,552
2203.05604	Deep Learning-Based Perceptual Stimulus Encoder for Bionic Vision	Retinal implants have the potential to treat incurable blindness, yet the quality of the artificial vision they produce is still rudimentary. An outstanding challenge is identifying electrode activation patterns that lead to intelligible visual percepts (phosphenes). Here we propose a PSE based on CNN that is trained i...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	284,853
cs/9709102	Identifying Hierarchical Structure in Sequences: A linear-time algorithm	SEQUITUR is an algorithm that infers a hierarchical structure from a sequence of discrete symbols by replacing repeated phrases with a grammatical rule that generates the phrase, and continuing this process recursively. The result is a hierarchical representation of the original sequence, which offers insights into its...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	540,367
2004.05722	Complaint-driven Training Data Debugging for Query 2.0	As the need for machine learning (ML) increases rapidly across all industry sectors, there is a significant interest among commercial database providers to support "Query 2.0", which integrates model inference into SQL queries. Debugging Query 2.0 is very challenging since an unexpected query result may be caused by th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	172,288
1711.03640	Stochastic Deep Learning in Memristive Networks	We study the performance of stochastically trained deep neural networks (DNNs) whose synaptic weights are implemented using emerging memristive devices that exhibit limited dynamic range, resolution, and variability in their programming characteristics. We show that a key device parameter to optimize the learning effic...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	84,252
2406.15488	Orangutan: A Multiscale Brain Emulation-Based Artificial Intelligence Framework for Dynamic Environments	Achieving General Artificial Intelligence (AGI) has long been a grand challenge in the field of AI, and brain-inspired computing is widely acknowledged as one of the most promising approaches to realize this goal. This paper introduces a novel brain-inspired AI framework, Orangutan. It simulates the structure and compu...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	466,749
1102.4599	Towards Unbiased BFS Sampling	Breadth First Search (BFS) is a widely used approach for sampling large unknown Internet topologies. Its main advantage over random walks and other exploration techniques is that a BFS sample is a plausible graph on its own, and therefore we can study its topological characteristics. However, it has been empirically ob...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	9,318
1907.01642	Introducing MathQA -- A Math-Aware Question Answering System	We present an open source math-aware Question Answering System based on Ask Platypus. Our system returns as a single mathematical formula for a natural language question in English or Hindi. This formulae originate from the knowledge-base Wikidata. We translate these formulae to computable data by integrating the calcu...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	true	137,383
2003.11227	Logarithmic Regret Bound in Partially Observable Linear Dynamical Systems	We study the problem of system identification and adaptive control in partially observable linear dynamical systems. Adaptive and closed-loop system identification is a challenging problem due to correlations introduced in data collection. In this paper, we present the first model estimation method with finite-time gua...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	169,548
2201.07265	EP-PQM: Efficient Parametric Probabilistic Quantum Memory with Fewer Qubits and Gates	Machine learning (ML) classification tasks can be carried out on a quantum computer (QC) using Probabilistic Quantum Memory (PQM) and its extension, Parameteric PQM (P-PQM) by calculating the Hamming distance between an input pattern and a database of $r$ patterns containing $z$ features with $a$ distinct attributes. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	275,977
2010.07367	Pose Refinement Graph Convolutional Network for Skeleton-based Action Recognition	With the advances in capturing 2D or 3D skeleton data, skeleton-based action recognition has received an increasing interest over the last years. As skeleton data is commonly represented by graphs, graph convolutional networks have been proposed for this task. While current graph convolutional networks accurately recog...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	200,784
1808.08478	Network Inference from Temporal-Dependent Grouped Observations	In social network analysis, the observed data is usually some social behavior, such as the formation of groups, rather than an explicit network structure. Zhao and Weko (2017) propose a model-based approach called the hub model to infer implicit networks from grouped observations. The hub model assumes independence bet...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	105,958
1806.07439	HybridNet: Integrating Model-based and Data-driven Learning to Predict Evolution of Dynamical Systems	The robotic systems continuously interact with complex dynamical systems in the physical world. Reliable predictions of spatiotemporal evolution of these dynamical systems, with limited knowledge of system dynamics, are crucial for autonomous operation. In this paper, we present HybridNet, a framework that integrates d...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	100,926
2204.04009	On Projectivity in Markov Logic Networks	Markov Logic Networks (MLNs) define a probability distribution on relational structures over varying domain sizes. Many works have noticed that MLNs, like many other relational models, do not admit consistent marginal inference over varying domain sizes. Furthermore, MLNs learnt on a certain domain do not generalize to...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	290,506
1312.7650	On the Minimum Decoding Delay of Balanced Complex Orthogonal Design	Complex orthogonal design (COD) with parameter $[p, n, k]$ is a combinatorial design used in space-time block codes (STBCs). For STBC, $n$ is the number of antennas, $k/p$ is the rate, and $p$ is the decoding delay. A class of rate $1/2$ COD called balanced complex orthogonal design (BCOD) has been proposed by Adams et...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	29,505
2009.02827	MFL_COVID19: Quantifying Country-based Factors affecting Case Fatality Rate in Early Phase of COVID-19 Epidemic via Regularised Multi-task Feature Learning	Recent outbreak of COVID-19 has led a rapid global spread around the world. Many countries have implemented timely intensive suppression to minimize the infections, but resulted in high case fatality rate (CFR) due to critical demand of health resources. Other country-based factors such as sociocultural issues, ageing ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	194,672
2304.00436	Instance-Level Trojan Attacks on Visual Question Answering via Adversarial Learning in Neuron Activation Space	Trojan attacks embed perturbations in input data leading to malicious behavior in neural network models. A combination of various Trojans in different modalities enables an adversary to mount a sophisticated attack on multimodal learning such as Visual Question Answering (VQA). However, multimodal Trojans in convention...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	355,687
1706.04829	The way to uncover community structure with core and diversity	Communities are ubiquitous in nature and society. Individuals that share common properties often self-organize to form communities. Avoiding the shortages of computation complexity, pre-given information and unstable results in different run, in this paper, we propose a simple and effcient method to deepen our understa...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	75,402
1611.05358	Lip Reading Sentences in the Wild	The goal of this work is to recognise phrases and sentences being spoken by a talking face, with or without the audio. Unlike previous works that have focussed on recognising a limited number of words or phrases, we tackle lip reading as an open-world problem - unconstrained natural language sentences, and in the wild ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	64,000
1705.10986	Class Specific Feature Selection for Interval Valued Data Through Interval K-Means Clustering	In this paper, a novel feature selection approach for supervised interval valued features is proposed. The proposed approach takes care of selecting the class specific features through interval K-Means clustering. The kernel of K-Means clustering algorithm is modified to adapt interval valued data. During training, a s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	74,512
2006.06372	TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation	Thompson sampling has become a ubiquitous approach to online decision problems with bandit feedback. The key algorithmic task for Thompson sampling is drawing a sample from the posterior of the optimal action. We propose an alternative arm selection rule we dub TS-UCB, that requires negligible additional computational ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,407
2007.04281	Reconfigurable Intelligent Surfaces Empowered THz Communication in LEO Satellite Networks	The revolution in the low Earth orbit (LEO) satellite networks will bring changes on their communication models and a shift from the classical bent-pipe architectures to more sophisticated networking platforms. Thanks to technological advancements in microelectronics and micro-systems, the terahertz (THz) band has emer...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	186,309
1811.12006	Global Second-order Pooling Convolutional Networks	Deep Convolutional Networks (ConvNets) are fundamental to, besides large-scale visual recognition, a lot of vision tasks. As the primary goal of the ConvNets is to characterize complex boundaries of thousands of classes in a high-dimensional space, it is critical to learn higher-order representations for enhancing non-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	114,910
2108.04555	Deep Joint Learning of Pathological Region Localization and Alzheimer's Disease Diagnosis	The identification of Alzheimer's disease (AD) and its early stages using structural magnetic resonance imaging (MRI) has been attracting the attention of researchers. Various data-driven approaches have been introduced to capture subtle and local morphological changes of the brain accompanied by the disease progressio...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	250,044
2109.07782	An Open Problem on Sparse Representations in Unions of Bases	We consider sparse representations of signals from redundant dictionaries which are unions of several orthonormal bases. The spark introduced by Donoho and Elad plays an important role in sparse representations. However, numerical computations of sparks are generally combinatorial. For unions of several orthonormal bas...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	255,653
2403.11865	Exploring Multi-modal Neural Scene Representations With Applications on Thermal Imaging	Neural Radiance Fields (NeRFs) quickly evolved as the new de-facto standard for the task of novel view synthesis when trained on a set of RGB images. In this paper, we conduct a comprehensive evaluation of neural scene representations, such as NeRFs, in the context of multi-modal learning. Specifically, we present four...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	438,899
1809.07609	Machine Learning for semi linear PDEs	Recent machine learning algorithms dedicated to solving semi-linear PDEs are improved by using different neural network architectures and different parameterizations. These algorithms are compared to a new one that solves a fixed point problem by using deep learning techniques. This new algorithm appears to be competit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	108,311
2212.10152	Quirk or Palmer: A Comparative Study of Modal Verb Frameworks with Annotated Datasets	Modal verbs, such as "can", "may", and "must", are commonly used in daily communication to convey the speaker's perspective related to the likelihood and/or mode of the proposition. They can differ greatly in meaning depending on how they're used and the context of a sentence (e.g. "They 'must' help each other out." vs...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,356
2307.13831	Relationship between Batch Size and Number of Steps Needed for Nonconvex Optimization of Stochastic Gradient Descent using Armijo Line Search	While stochastic gradient descent (SGD) can use various learning rates, such as constant or diminishing rates, the previous numerical results showed that SGD performs better than other deep learning optimizers using when it uses learning rates given by line search methods. In this paper, we perform a convergence analys...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	381,713
1708.01405	{\mu}-MAR: Multiplane 3D Marker based Registration for Depth-sensing Cameras	Many applications including object reconstruction, robot guidance, and scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown an it is necessary to apply expert inference to estimate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,380
2410.12694	VividMed: Vision Language Model with Versatile Visual Grounding for Medicine	Recent advancements in Vision Language Models (VLMs) have demonstrated remarkable promise in generating visually grounded responses. However, their application in the medical domain is hindered by unique challenges. For instance, most VLMs rely on a single method of visual grounding, whereas complex medical tasks deman...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	499,148
2311.07595	A Decision Support System for Liver Diseases Prediction: Integrating Batch Processing, Rule-Based Event Detection and SPARQL Query	Liver diseases pose a significant global health burden, impacting a substantial number of individuals and exerting substantial economic and social consequences. Rising liver problems are considered a fatal disease in many countries, such as Egypt, Molda, etc. The objective of this study is to construct a predictive mod...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	407,396
1501.04725	Learning Invariants using Decision Trees	The problem of inferring an inductive invariant for verifying program safety can be formulated in terms of binary classification. This is a standard problem in machine learning: given a sample of good and bad points, one is asked to find a classifier that generalizes from the sample and separates the two sets. Here, th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	39,408
1902.09834	Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets	Learning predictive models from small high-dimensional data sets is a key problem in high-dimensional statistics. Expert knowledge elicitation can help, and a strong line of work focuses on directly eliciting informative prior distributions for parameters. This either requires considerable statistical expertise or is l...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	122,517
1612.07976	DeMIAN: Deep Modality Invariant Adversarial Network	Obtaining common representations from different modalities is important in that they are interchangeable with each other in a classification problem. For example, we can train a classifier on image features in the common representations and apply it to the testing of the text features in the representations. Existing m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	66,010
2103.11364	Schr\"odinger's Ballot: Quantum Information and the Violation of Arrow's Impossibility Theorem	In this paper we study Arrow's Impossibility Theorem in the quantum setting. Our work is based on the work of Bao and Halpern, in which it is proved that the quantum analogue of Arrow's Impossibility Theorem is not valid. However, we feel unsatisfied about the proof presented there. Moreover, the definition of Quantum ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	225,782
1905.09922	Training language GANs from Scratch	Generative Adversarial Networks (GANs) enjoy great success at image generation, but have proven difficult to train in the domain of natural language. Challenges with gradient estimation, optimization instability, and mode collapse have lead practitioners to resort to maximum likelihood pre-training, followed by small a...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	131,881
2110.12997	Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning	Unsupervised reinforcement learning aims to acquire skills without prior goal representations, where an agent automatically explores an open-ended environment to represent goals and learn the goal-conditioned policy. However, this procedure is often time-consuming, limiting the rollout in some potentially expensive tar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	263,040
2212.06414	Even Order Explicit Symplectic Geometric Algorithms for Solving Quaternions in Guidance Navigation and Control via Diagonal Pad\'{e} Approximation and Cayley Transform	Quaternion kinematical differential equation (QKDE) plays a key role in navigation, control and guidance systems. Although explicit symplectic geometric algorithms (ESGA) for this problem are available, there is a lack of a unified way for constructing high order symplectic difference schemes with configurable order pa...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	336,108
2402.12653	Unbiased Estimation for Total Treatment Effect Under Interference Using Aggregated Dyadic Data	In social media platforms, user behavior is often influenced by interactions with other users, complicating the accurate estimation of causal effects in traditional A/B experiments. This study investigates situations where an individual's outcome can be broken down into the sum of multiple pairwise outcomes, a reflecti...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	430,928
2001.02656	Stochastic Probabilistic Programs	We introduce the notion of a stochastic probabilistic program and present a reference implementation of a probabilistic programming facility supporting specification of stochastic probabilistic programs and inference in them. Stochastic probabilistic programs allow straightforward specification and efficient inference ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	159,784
1808.06220	Jointly Deep Multi-View Learning for Clustering Analysis	In this paper, we propose a novel Joint framework for Deep Multi-view Clustering (DMJC), where multiple deep embedded features, multi-view fusion mechanism and clustering assignments can be learned simultaneously. Our key idea is that the joint learning strategy can sufficiently exploit clustering-friendly multi-view f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	105,491
1409.6883	Performance Analysis of Faults Detection in Wind Turbine Generator Based on High-Resolution Frequency Estimation Methods	Electrical energy production based on wind power has become the most popular renewable resources in the recent years because it gets reliable clean energy with minimum cost. The major challenge for wind turbines is the electrical and the mechanical failures which can occur at any time causing prospective breakdowns and...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	36,279
1806.06720	An Online Prediction Algorithm for Reinforcement Learning with Linear Function Approximation using Cross Entropy Method	In this paper, we provide two new stable online algorithms for the problem of prediction in reinforcement learning, \emph{i.e.}, estimating the value function of a model-free Markov reward process using the linear function approximation architecture and with memory and computation costs scaling quadratically in the siz...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	100,752
1512.06372	Optimizing Spread of Influence in Weighted Social Networks via Partial Incentives	A widely studied process of influence diffusion in social networks posits that the dynamics of influence diffusion evolves as follows: Given a graph $G=(V,E)$, representing the network, initially \emph{only} the members of a given $S\subseteq V$ are influenced; subsequently, at each round, the set of influenced nodes i...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	50,311
1912.04437	Design Trade-offs for Decentralized Baseband Processing in Massive MU-MIMO Systems	Massive multi-user (MU) multiple-input multiple-output (MIMO) provides high spectral efficiency by means of spatial multiplexing and fine-grained beamforming. However, conventional base-station (BS) architectures for systems with hundreds of antennas that rely on centralized baseband processing inevitably suffer from (...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	156,835
2212.12141	Human Activity Recognition in an Open World	Managing novelty in perception-based human activity recognition (HAR) is critical in realistic settings to improve task performance over time and ensure solution generalization outside of prior seen samples. Novelty manifests in HAR as unseen samples, activities, objects, environments, and sensor changes, among other w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	337,974
2208.06264	A Boring-yet-effective Approach for the Product Ranking Task of the Amazon KDD Cup 2022	In this work we describe our submission to the product ranking task of the Amazon KDD Cup 2022. We rely on a receipt that showed to be effective in previous competitions: we focus our efforts towards efficiently training and deploying large language odels, such as mT5, while reducing to a minimum the number of task-spe...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	312,658
2310.06068	Augmenting Vision-Based Human Pose Estimation with Rotation Matrix	Fitness applications are commonly used to monitor activities within the gym, but they often fail to automatically track indoor activities inside the gym. This study proposes a model that utilizes pose estimation combined with a novel data augmentation method, i.e., rotation matrix. We aim to enhance the classification ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	398,406
2309.06439	Attention De-sparsification Matters: Inducing Diversity in Digital Pathology Representation Learning	We propose DiRL, a Diversity-inducing Representation Learning technique for histopathology imaging. Self-supervised learning techniques, such as contrastive and non-contrastive approaches, have been shown to learn rich and effective representations of digitized tissue samples with limited pathologist supervision. Our a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,418
2410.19493	Conditional Hallucinations for Image Compression	In lossy image compression, models face the challenge of either hallucinating details or generating out-of-distribution samples due to the information bottleneck. This implies that at times, introducing hallucinations is necessary to generate in-distribution samples. The optimal level of hallucination varies depending ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	502,339
2403.17381	Application-Driven Innovation in Machine Learning	As applications of machine learning proliferate, innovative algorithms inspired by specific real-world challenges have become increasingly important. Such work offers the potential for significant impact not merely in domains of application but also in machine learning itself. In this paper, we describe the paradigm of...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	441,442
2303.15258	Unconditionally secure ciphers with a short key for a source with unknown statistics	We consider the problem of constructing an unconditionally secure cipher with a short key for the case where the probability distribution of encrypted messages is unknown. Note that unconditional security means that an adversary with no computational constraints can obtain only a negligible amount of information ("leak...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	354,426
2206.11073	A Unified and Biologically-Plausible Relational Graph Representation of Vision Transformers	Vision transformer (ViT) and its variants have achieved remarkable successes in various visual tasks. The key characteristic of these ViT models is to adopt different aggregation strategies of spatial patch information within the artificial neural networks (ANNs). However, there is still a key lack of unified represent...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false	false	304,145
q-bio/0607018	A p-Adic Model of DNA Sequence and Genetic Code	Using basic properties of p-adic numbers, we consider a simple new approach to describe main aspects of DNA sequence and genetic code. Central role in our investigation plays an ultrametric p-adic information space which basic elements are nucleotides, codons and genes. We show that a 5-adic model is appropriate for DN...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,856
2410.21896	Evaluating K-Fold Cross Validation for Transformer Based Symbolic Regression Models	Symbolic Regression remains an NP-Hard problem, with extensive research focusing on AI models for this task. Transformer models have shown promise in Symbolic Regression, but performance suffers with smaller datasets. We propose applying k-fold cross-validation to a transformer-based symbolic regression model trained o...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	503,427
2308.13266	Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and Segmentation	Tracking any given object(s) spatially and temporally is a common purpose in Visual Object Tracking (VOT) and Video Object Segmentation (VOS). Joint tracking and segmentation have been attempted in some studies but they often lack full compatibility of both box and mask in initialization and prediction, and mainly focu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,849
2112.07194	MDD-Eval: Self-Training on Augmented Data for Multi-Domain Dialogue Evaluation	Chatbots are designed to carry out human-like conversations across different domains, such as general chit-chat, knowledge exchange, and persona-grounded conversations. To measure the quality of such conversational agents, a dialogue evaluator is expected to conduct assessment across domains as well. However, most of t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	271,404
1401.4273	Nuclear Norm Subspace Identification (N2SID) for short data batches	Subspace identification is revisited in the scope of nuclear norm minimization methods. It is shown that essential structural knowledge about the unknown data matrices in the data equation that relates Hankel matrices constructed from input and output data can be used in the first step of the numerical solution present...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	30,059
2304.14773	Synergy of Machine and Deep Learning Models for Multi-Painter Recognition	The growing availability of digitized art collections has created the need to manage, analyze and categorize large amounts of data related to abstract concepts, highlighting a demanding problem of computer science and leading to new research perspectives. Advances in artificial intelligence and neural networks provide ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	361,088
1910.12740	Sequence-to-sequence Automatic Speech Recognition with Word Embedding Regularization and Fused Decoding	In this paper, we investigate the benefit that off-the-shelf word embedding can bring to the sequence-to-sequence (seq-to-seq) automatic speech recognition (ASR). We first introduced the word embedding regularization by maximizing the cosine similarity between a transformed decoder feature and the target word embedding...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	151,184
1412.2188	Concurrent Bursty Behavior of Social Sensors in Sporting Events	The advent of social media expands our ability to transmit information and connect with others instantly, which enables us to behave as "social sensors." Here, we studied concurrent bursty behavior of Twitter users during major sporting events to determine their function as social sensors. We show that the degree of co...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	38,175
2303.02343	What Is Missing in IRM Training and Evaluation? Challenges and Solutions	Invariant risk minimization (IRM) has received increasing attention as a way to acquire environment-agnostic data representations and predictions, and as a principled solution for preventing spurious correlations from being learned and for improving models' out-of-distribution generalization. Yet, recent works have fou...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	349,318
2312.15548	YAYI-UIE: A Chat-Enhanced Instruction Tuning Framework for Universal Information Extraction	The difficulty of the information extraction task lies in dealing with the task-specific label schemas and heterogeneous data structures. Recent work has proposed methods based on large language models to uniformly model different information extraction tasks. However, these existing methods are deficient in their info...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	418,043
1203.3274	Two kinds of Phase transitions in a Voting model	In this paper, we discuss a voting model with two candidates, C_0 and C_1. We consider two types of voters--herders and independents. The voting of independents is based on their fundamental values; on the other hand, the voting of herders is based on the number of previous votes. We can identify two kinds of phase tra...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	14,896
2302.10167	Cross-domain Compositing with Pretrained Diffusion Models	Diffusion models have enabled high-quality, conditional image editing capabilities. We propose to expand their arsenal, and demonstrate that off-the-shelf diffusion models can be used for a wide range of cross-domain compositing tasks. Among numerous others, these include image blending, object immersion, texture-repla...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	346,694
1802.06924	Teaching Categories to Human Learners with Visual Explanations	We study the problem of computer-assisted teaching with explanations. Conventional approaches for machine teaching typically only provide feedback at the instance level e.g., the category or label of the instance. However, it is intuitive that clear explanations from a knowledgeable teacher can significantly improve a ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	90,782
2207.14502	Language Models Can Teach Themselves to Program Better	Recent Language Models (LMs) achieve breakthrough performance in code generation when trained on human-authored problems, even solving some competitive-programming problems. Self-play has proven useful in games such as Go, and thus it is natural to ask whether LMs can generate their own instructive programming problems...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	310,610
2303.12643	Traffic Volume Prediction using Memory-Based Recurrent Neural Networks: A comparative analysis of LSTM and GRU	Predicting traffic volume in real-time can improve both traffic flow and road safety. A precise traffic volume forecast helps alert drivers to the flow of traffic along their preferred routes, preventing potential deadlock situations. Existing parametric models cannot reliably forecast traffic volume in dynamic and com...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	353,323
2009.06078	Random boosting and random^2 forests -- A random tree depth injection approach	The induction of additional randomness in parallel and sequential ensemble methods has proven to be worthwhile in many aspects. In this manuscript, we propose and examine a novel random tree depth injection approach suitable for sequential and parallel tree-based approaches including Boosting and Random Forests. The re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	195,519
2203.01110	The Optimal Noise in Noise-Contrastive Learning Is Not What You Think	Learning a parametric model of a data distribution is a well-known statistical problem that has seen renewed interest as it is brought to scale in deep learning. Framing the problem as a self-supervised task, where data samples are discriminated from noise samples, is at the core of state-of-the-art methods, beginning ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	283,255
2307.12970	Volcanic ash delimitation using Artificial Intelligence based on Pix2Pix	Volcanic eruptions emit ash that can be harmful to human health and cause damage to infrastructure, economic activities and the environment. The delimitation of ash clouds allows to know their behavior and dispersion, which helps in the prevention and mitigation of this phenomenon. Traditional methods take advantage of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	381,440
1902.03111	High-resolution home location prediction from tweets using deep learning with dynamic structure	Timely and high-resolution estimates of the home locations of a sufficiently large subset of the population are critical for effective disaster response and public health intervention, but this is still an open problem. Conventional data sources, such as census and surveys, have a substantial time lag and cannot captur...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	121,027
1809.11127	RoboCup 2016 Humanoid TeenSize Winner NimbRo: Robust Visual Perception and Soccer Behaviors	The trend in the RoboCup Humanoid League rules over the past few years has been towards a more realistic and challenging game environment. Elementary skills such as visual perception and walking, which had become mature enough for exciting gameplay, are now once again core challenges. The field goals are both white, an...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	109,061
2403.18985	Robustness and Visual Explanation for Black Box Image, Video, and ECG Signal Classification with Reinforcement Learning	We present a generic Reinforcement Learning (RL) framework optimized for crafting adversarial attacks on different model types spanning from ECG signal analysis (1D), image classification (2D), and video classification (3D). The framework focuses on identifying sensitive regions and inducing misclassifications with min...	false	false	false	false	true	false	true	false	false	false	false	true	true	false	true	false	false	false	442,153
2106.02965	Extracting Weighted Automata for Approximate Minimization in Language Modelling	In this paper we study the approximate minimization problem for language modelling. We assume we are given some language model as a black box. The objective is to obtain a weighted finite automaton (WFA) that fits within a given size constraint and which mimics the behaviour of the original model while minimizing some ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	239,106
2004.15001	Don't Use English Dev: On the Zero-Shot Cross-Lingual Evaluation of Contextual Embeddings	Multilingual contextual embeddings have demonstrated state-of-the-art performance in zero-shot cross-lingual transfer learning, where multilingual BERT is fine-tuned on one source language and evaluated on a different target language. However, published results for mBERT zero-shot accuracy vary as much as 17 points on ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	175,081
2204.05814	MuCoT: Multilingual Contrastive Training for Question-Answering in Low-resource Languages	Accuracy of English-language Question Answering (QA) systems has improved significantly in recent years with the advent of Transformer-based models (e.g., BERT). These models are pre-trained in a self-supervised fashion with a large English text corpus and further fine-tuned with a massive English QA dataset (e.g., SQu...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	291,151
2303.02879	A Review of Deep Learning-Powered Mesh Reconstruction Methods	With the recent advances in hardware and rendering techniques, 3D models have emerged everywhere in our life. Yet creating 3D shapes is arduous and requires significant professional knowledge. Meanwhile, Deep learning has enabled high-quality 3D shape reconstruction from various sources, making it a viable approach to ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	349,519
2110.06328	Quadrotor going through a window and landing: An image-based visual servo control approach	This paper considers the problem of controlling a quadrotor to go through a window and land on a planar target, the landing pad, using an Image-Based Visual Servo (IBVS) controller that relies on sensing information from two on-board cameras and an IMU. The maneuver is divided into two stages: crossing the window and l...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	260,566
2012.12604	Dynamics of a Stratified Population of Optimum Seeking Agents on a Network -- Part II: Steady State Analysis	In this second part of our work, we study the steady state of the population and the social utility for the three dynamics SSD, NBRD and NRPM; which were introduced in the first part. We provide sufficient conditions on the network based on a maximum payoff density parameter of each node under which there exists a uniq...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	212,993

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.