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
2104.02547	Temporal-Logic-Based Intermittent, Optimal, and Safe Continuous-Time Learning for Trajectory Tracking	In this paper, we develop safe reinforcement-learning-based controllers for systems tasked with accomplishing complex missions that can be expressed as linear temporal logic specifications, similar to those required by search-and-rescue missions. We decompose the original mission into a sequence of tracking sub-problem...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	228,757
2406.04145	Every Answer Matters: Evaluating Commonsense with Probabilistic Measures	Large language models have demonstrated impressive performance on commonsense tasks; however, these tasks are often posed as multiple-choice questions, allowing models to exploit systematic biases. Commonsense is also inherently probabilistic with multiple correct answers. The purpose of "boiling water" could be making...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	461,540
2412.06836	GRUvader: Sentiment-Informed Stock Market Prediction	Stock price prediction is challenging due to global economic instability, high volatility, and the complexity of financial markets. Hence, this study compared several machine learning algorithms for stock market prediction and further examined the influence of a sentiment analysis indicator on the prediction of stock p...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	515,405
2204.04220	Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment	Deep Neural Networks (DNNs) have gained considerable attention in the past decades due to their astounding performance in different applications, such as natural language modeling, self-driving assistance, and source code understanding. With rapid exploration, more and more complex DNN architectures have been proposed ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	290,580
2304.09528	Network Algebraization and Port Relationship for Power-Electronic-Dominated Power Systems	Different from the quasi-static network in the traditional power system, the dynamic network in the power-electronic-dominated power system should be considered due to rapid response of converters' controls. In this paper, a nonlinear differential-algebraic model framework is established with algebraic equations for dy...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	359,084
1901.09469	Tangled String for Multi-Scale Explanation of Contextual Shifts in Stock Market	The original research question here is given by marketers in general, i.e., how to explain the changes in the desired timescale of the market. Tangled String, a sequence visualization tool based on the metaphor where contexts in a sequence are compared to tangled pills in a string, is here extended and diverted to dete...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	119,755
2501.05835	Fine-tuning is Not Fine: Mitigating Backdoor Attacks in GNNs with Limited Clean Data	Graph Neural Networks (GNNs) have achieved remarkable performance through their message-passing mechanism. However, recent studies have highlighted the vulnerability of GNNs to backdoor attacks, which can lead the model to misclassify graphs with attached triggers as the target class. The effectiveness of recent promis...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	523,741
2108.06830	'Walking Into a Fire Hoping You Don't Catch': Strategies and Designs to Facilitate Cross-Partisan Online Discussions	While cross-partisan conversations are central to a vibrant democracy, these are hard conversations to have, especially in the United States amidst unprecedented levels of partisan animosity. Such interactions often devolve into name-calling and personal attacks. We report on a qualitative study of 17 US residents who ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	250,736
2502.12659	The Hidden Risks of Large Reasoning Models: A Safety Assessment of R1	The rapid development of large reasoning models, such as OpenAI-o3 and DeepSeek-R1, has led to significant improvements in complex reasoning over non-reasoning large language models~(LLMs). However, their enhanced capabilities, combined with the open-source access of models like DeepSeek-R1, raise serious safety concer...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	534,992
2501.12620	Adaptive Data Exploitation in Deep Reinforcement Learning	We introduce ADEPT: Adaptive Data ExPloiTation, a simple yet powerful framework to enhance the data efficiency and generalization in deep reinforcement learning (RL). Specifically, ADEPT adaptively manages the use of sampled data across different learning stages via multi-armed bandit (MAB) algorithms, optimizi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	526,383
2109.00036	Half-Space and Box Constraints as NUV Priors: First Results	Normals with unknown variance (NUV) can represent many useful priors and blend well with Gaussian models and message passing algorithms. NUV representations of sparsifying priors have long been known, and NUV representations of binary (and M-level) priors have been proposed very recently. In this document, we propose N...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	252,982
2402.09075	Steady-State Error Compensation for Reinforcement Learning with Quadratic Rewards	The selection of a reward function in Reinforcement Learning (RL) has garnered significant attention because of its impact on system performance. Issues of significant steady-state errors often manifest when quadratic reward functions are employed. Although absolute-value-type reward functions alleviate this problem, t...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	429,355
1711.04352	Fast Reading Comprehension with ConvNets	State-of-the-art deep reading comprehension models are dominated by recurrent neural nets. Their sequential nature is a natural fit for language, but it also precludes parallelization within an instances and often becomes the bottleneck for deploying such models to latency critical scenarios. This is particularly probl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	84,383
2409.06429	Human-mimetic binaural ear design and sound source direction estimation for task realization of musculoskeletal humanoids	Human-like environment recognition by musculoskeletal humanoids is important for task realization in real complex environments and for use as dummies for test subjects. Humans integrate various sensory information to perceive their surroundings, and hearing is particularly useful for recognizing objects out of view or ...	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	487,123
2107.14768	Debiased Explainable Pairwise Ranking from Implicit Feedback	Recent work in recommender systems has emphasized the importance of fairness, with a particular interest in bias and transparency, in addition to predictive accuracy. In this paper, we focus on the state of the art pairwise ranking model, Bayesian Personalized Ranking (BPR), which has previously been found to outperfor...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	248,562
2501.09731	Predictions as Surrogates: Revisiting Surrogate Outcomes in the Age of AI	We establish a formal connection between the decades-old surrogate outcome model in biostatistics and economics and the emerging field of prediction-powered inference (PPI). The connection treats predictions from pre-trained models, prevalent in the age of AI, as cost-effective surrogates for expensive outcomes. Buildi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	525,247
1303.6378	Linear complexity of generalized cyclotomic sequences of order 4 over F_l	Generalized cyclotomic sequences of period pq have several desirable randomness properties if the two primes p and q are chosen properly. In particular,Ding deduced the exact formulas for the autocorrelation and the linear complexity of these sequences of order 2. In this paper, we consider the generalized sequences of...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	23,268
2202.06830	Online Approval Committee Elections	Assume $k$ candidates need to be selected. The candidates appear over time. Each time one appears, it must be immediately selected or rejected -- a decision that is made by a group of individuals through voting. Assume the voters use approval ballots, i.e., for each candidate they only specify whether they consider it ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	280,348
2203.02227	Partial Wasserstein Adversarial Network for Non-rigid Point Set Registration	Given two point sets, the problem of registration is to recover a transformation that matches one set to the other. This task is challenging due to the presence of the large number of outliers, the unknown non-rigid deformations and the large sizes of point sets. To obtain strong robustness against outliers, we formula...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	283,689
1811.07056	Domain Adaptive Transfer Learning with Specialist Models	Transfer learning is a widely used method to build high performing computer vision models. In this paper, we study the efficacy of transfer learning by examining how the choice of data impacts performance. We find that more pre-training data does not always help, and transfer performance depends on a judicious choice o...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	113,655
2101.07069	Emotional EEG Classification using Connectivity Features and Convolutional Neural Networks	Convolutional neural networks (CNNs) are widely used to recognize the user's state through electroencephalography (EEG) signals. In the previous studies, the EEG signals are usually fed into the CNNs in the form of high-dimensional raw data. However, this approach makes it difficult to exploit the brain connectivity in...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	215,932
1403.5290	Nonlinear Feedback Control of Axisymmetric Aerial Vehicles	We investigate the use of simple aerodynamic models for the feedback control of aerial vehicles with large flight envelopes. Thrust-propelled vehicles with a body shape symmetric with respect to the thrust axis are considered. Upon a condition on the aerodynamic characteristics of the vehicle, we show that the equilibr...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	31,712
2111.06268	Raman spectroscopy in open world learning settings using the Objectosphere approach	Raman spectroscopy in combination with machine learning has significant promise for applications in clinical settings as a rapid, sensitive, and label-free identification method. These approaches perform well in classifying data that contains classes that occur during the training phase. However, in practice, there are...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	266,027
2310.01055	Improved Crop and Weed Detection with Diverse Data Ensemble Learning	Modern agriculture heavily relies on Site-Specific Farm Management practices, necessitating accurate detection, localization, and quantification of crops and weeds in the field, which can be achieved using deep learning techniques. In this regard, crop and weed-specific binary segmentation models have shown promise. Ho...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	396,260
1604.04730	Evolutionary-aided negotiation model for bilateral bargaining in Ambient Intelligence domains with complex utility functions	Ambient Intelligence aims to offer personalized services and easier ways of interaction between people and systems. Since several users and systems may coexist in these environments, it is quite possible that entities with opposing preferences need to cooperate to reach their respective goals. Automated negotiation is ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	true	54,697
2101.11360	An Empirical Study of Cross-Lingual Transferability in Generative Dialogue State Tracker	There has been a rapid development in data-driven task-oriented dialogue systems with the benefit of large-scale datasets. However, the progress of dialogue systems in low-resource languages lags far behind due to the lack of high-quality data. To advance the cross-lingual technology in building dialog systems, DSTC9 i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	217,252
2406.12440	Deep self-supervised learning with visualisation for automatic gesture recognition	Gesture is an important mean of non-verbal communication, with visual modality allows human to convey information during interaction, facilitating peoples and human-machine interactions. However, it is considered difficult to automatically recognise gestures. In this work, we explore three different means to recognise ...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	465,411
1404.7467	Coupled Matrix Factorization within Non-IID Context	Recommender systems research has experienced different stages such as from user preference understanding to content analysis. Typical recommendation algorithms were built on the following bases: (1) assuming users and items are IID, namely independent and identically distributed, and (2) focusing on specific aspects su...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	32,691
1712.06787	Model Predictive BESS Control for Demand Charge Management and PV-Utilization Improvement	Adoption of battery energy storage systems for behind-the-meters application offers valuable benefits for demand charge management as well as increasing PV-utilization. The key point is that while the benefit/cost ratio for a single application may not be favorable for economic benefits of storage systems, stacked serv...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	86,934
2005.10224	The Random Feature Model for Input-Output Maps between Banach Spaces	Well known to the machine learning community, the random feature model is a parametric approximation to kernel interpolation or regression methods. It is typically used to approximate functions mapping a finite-dimensional input space to the real line. In this paper, we instead propose a methodology for use of the rand...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	178,124
1812.09476	Event-triggered consensus of multi-agent systems under directed topology based on periodic sampled-data	The event-triggered consensus problem of first-order multi-agent systems under directed topology is investigated. The event judgements are only implemented at periodic time instants. Under the designed consensus algorithm, the sampling period is permitted to be arbitrarily large. Another advantage of the designed conse...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	117,159
2209.09570	Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design	Attention-based neural networks have become pervasive in many AI tasks. Despite their excellent algorithmic performance, the use of the attention mechanism and feed-forward network (FFN) demands excessive computational and memory resources, which often compromises their hardware performance. Although various sparse var...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	318,558
2309.08180	AVM-SLAM: Semantic Visual SLAM with Multi-Sensor Fusion in a Bird's Eye View for Automated Valet Parking	Accurate localization in challenging garage environments -- marked by poor lighting, sparse textures, repetitive structures, dynamic scenes, and the absence of GPS -- is crucial for automated valet parking (AVP) tasks. Addressing these challenges, our research introduces AVM-SLAM, a cutting-edge semantic visual SLAM ar...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	392,069
1904.08959	RepGN:Object Detection with Relational Proposal Graph Network	Region based object detectors achieve the state-of-the-art performance, but few consider to model the relation of proposals. In this paper, we explore the idea of modeling the relationships among the proposals for object detection from the graph learning perspective. Specifically, we present relational proposal graph n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	128,227
2110.07588	Playing for 3D Human Recovery	Image- and video-based 3D human recovery (i.e., pose and shape estimation) have achieved substantial progress. However, due to the prohibitive cost of motion capture, existing datasets are often limited in scale and diversity. In this work, we obtain massive human sequences by playing the video game with automatically ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	261,050
1709.00670	Difficulty-level Modeling of Ontology-based Factual Questions	Semantics based knowledge representations such as ontologies are found to be very useful in automatically generating meaningful factual questions. Determining the difficulty level of these system generated questions is helpful to effectively utilize them in various educational and professional applications. The existin...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	79,951
2305.08298	Symbol tuning improves in-context learning in language models	We present symbol tuning - finetuning language models on in-context input-label pairs where natural language labels (e.g., "positive/negative sentiment") are replaced with arbitrary symbols (e.g., "foo/bar"). Symbol tuning leverages the intuition that when a model cannot use instructions or natural language labels to f...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	364,234
2410.16731	RIS-Assisted THz MIMO Wireless System in the Presence of Direct Link for CV-QKD with Limited Quantum Memory	A reconfigurable intelligent surface (RIS)-aided multiple-input multiple-output (MIMO) wireless communication system is considered in this paper wherein the transmitter, Alice modulates secret keys, by using a continuous variable quantum key distribution technique to be transmitted to the receiver, Bob, which employs h...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	501,166
1606.01985	Adaptation is Useless for Two Discrete Additive-Noise Two-Way Channels	In two-way channels, each user transmits and receives at the same time. This allows each encoder to interactively adapt the current input to its own message and all previously received signals. Such coding approach can introduce correlation between inputs of different users, since all the users' outputs are correlated ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	56,889
2202.03519	Smoothed Online Optimization with Unreliable Predictions	We examine the problem of smoothed online optimization, where a decision maker must sequentially choose points in a normed vector space to minimize the sum of per-round, non-convex hitting costs and the costs of switching decisions between rounds. The decision maker has access to a black-box oracle, such as a machine l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	279,229
1304.0036	Tight bound on relative entropy by entropy difference	We prove a lower bound on the relative entropy between two finite-dimensional states in terms of their entropy difference and the dimension of the underlying space. The inequality is tight in the sense that equality can be attained for any prescribed value of the entropy difference, both for quantum and classical syste...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	23,363
2402.09450	Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram	Electrocardiograms (ECG) are widely employed as a diagnostic tool for monitoring electrical signals originating from a heart. Recent machine learning research efforts have focused on the application of screening various diseases using ECG signals. However, adapting to the application of screening disease is challenging...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	429,528
2205.08343	Moving Stuff Around: A study on efficiency of moving documents into memory for Neural IR models	When training neural rankers using Large Language Models, it's expected that a practitioner would make use of multiple GPUs to accelerate the training time. By using more devices, deep learning frameworks, like PyTorch, allow the user to drastically increase the available VRAM pool, making larger batches possible when ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	296,898
2104.14124	Condensation-Net: Memory-Efficient Network Architecture with Cross-Channel Pooling Layers and Virtual Feature Maps	"Lightweight convolutional neural networks" is an important research topic in the field of embedded vision. To implement image recognition tasks on a resource-limited hardware platform, it is necessary to reduce the memory size and the computational cost. The contribution of this paper is stated as follows. First, we p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	232,723
2208.12111	Runtime reliability monitoring for complex fault-tolerance policies	Reliability of complex Cyber-Physical Systems is necessary to guarantee availability and/or safety of the provided services. Diverse and complex fault tolerance policies are adopted to enhance reliability, that include a varied mix of redundancy and dynamic reconfiguration to address hardware reliability, as well as sp...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	314,627
2403.08525	From Weak to Strong Sound Event Labels using Adaptive Change-Point Detection and Active Learning	We propose an adaptive change point detection method (A-CPD) for machine guided weak label annotation of audio recording segments. The goal is to maximize the amount of information gained about the temporal activations of the target sounds. For each unlabeled audio recording, we use a prediction model to derive a proba...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	437,372
1407.1935	Fundamental Limits of Caching: Improved Bounds For Small Buffer Users	In this work, the peak rate of the caching problem is investigated, under the scenario that the users are with small buffer sizes and the number of users is no less than the amount of files in the server. A novel coded caching strategy is proposed for such a scenario, leading to a lower peak rate compared to recent res...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,482
1802.02871	Online Learning: A Comprehensive Survey	Online learning represents an important family of machine learning algorithms, in which a learner attempts to resolve an online prediction (or any type of decision-making) task by learning a model/hypothesis from a sequence of data instances one at a time. The goal of online learning is to ensure that the online learne...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	89,851
2112.14586	Isotuning With Applications To Scale-Free Online Learning	We extend and combine several tools of the literature to design fast, adaptive, anytime and scale-free online learning algorithms. Scale-free regret bounds must scale linearly with the maximum loss, both toward large losses and toward very small losses. Adaptive regret bounds demonstrate that an algorithm can take adva...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	273,567
0907.3493	Secure Network Coding for Wiretap Networks of Type II	We consider the problem of securing a multicast network against a wiretapper that can intercept the packets on a limited number of arbitrary network edges of its choice. We assume that the network employs the network coding technique to simultaneously deliver the packets available at the source to all the receivers. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,137
1507.03067	Micro-Clustering: Finding Small Clusters in Large Diversity	We address the problem of un-supervised soft-clustering called micro-clustering. The aim of the problem is to enumerate all groups composed of records strongly related to each other, while standard clustering methods separate records at sparse parts. The problem formulation of micro-clustering is non-trivial. Clique mi...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	45,047
1404.0077	Effective dimension in some general metric spaces	We introduce the concept of effective dimension for a wide class of metric spaces that are not required to have a computable measure. Effective dimension was defined by Lutz in (Lutz 2003) for Cantor space and has also been extended to Euclidean space. Lutz effectivization uses the concept of gale and supergale, our ex...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	31,979
1104.1825	Characterization of circulant graphs having perfect state transfer	In this paper we answer the question of when circulant quantum spin networks with nearest-neighbor couplings can give perfect state transfer. The network is described by a circulant graph $G$, which is characterized by its circulant adjacency matrix $A$. Formally, we say that there exists a {\it perfect state transfer}...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	9,933
1802.00233	On Polynomial time Constructions of Minimum Height Decision Tree	In this paper we study a polynomial time algorithms that for an input $A\subseteq {B_m}$ outputs a decision tree for $A$ of minimum depth. This problem has many applications that include, to name a few, computer vision, group testing, exact learning from membership queries and game theory. Arkin et al. and Moshkov ga...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	89,376
2105.11353	Change Point Detection in Nonstationary Sub-Hourly Wind Time Series	In this paper, we present a change point detection method for detecting change points in multivariate nonstationary wind speed time series. The change point method identifies changes in the covariance structure and decomposes the nonstationary multivariate time series into stationary segments. We also present parametri...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	236,675
2210.05046	Data-Driven Feedback Linearization using the Koopman Generator	This paper contributes a theoretical framework for data-driven feedback linearization of nonlinear control-affine systems. We unify the traditional geometric perspective on feedback linearization with an operator-theoretic perspective involving the Koopman operator. We first show that if the distribution of the control...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	322,676
1807.02371	End-to-End Race Driving with Deep Reinforcement Learning	We present research using the latest reinforcement learning algorithm for end-to-end driving without any mediated perception (object recognition, scene understanding). The newly proposed reward and learning strategies lead together to faster convergence and more robust driving using only RGB image from a forward facing...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	102,255
1904.06703	Dot-to-Dot: Explainable Hierarchical Reinforcement Learning for Robotic Manipulation	Robotic systems are ever more capable of automation and fulfilment of complex tasks, particularly with reliance on recent advances in intelligent systems, deep learning and artificial intelligence. However, as robots and humans come closer in their interactions, the matter of interpretability, or explainability of robo...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	127,615
2402.04896	Learning from the Best: Active Learning for Wireless Communications	Collecting an over-the-air wireless communications training dataset for deep learning-based communication tasks is relatively simple. However, labeling the dataset requires expert involvement and domain knowledge, may involve private intellectual properties, and is often computationally and financially expensive. Activ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	427,642
2212.01568	Generalizing Multiple Object Tracking to Unseen Domains by Introducing Natural Language Representation	Although existing multi-object tracking (MOT) algorithms have obtained competitive performance on various benchmarks, almost all of them train and validate models on the same domain. The domain generalization problem of MOT is hardly studied. To bridge this gap, we first draw the observation that the high-level informa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	334,481
0901.4012	Cross-situational and supervised learning in the emergence of communication	Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determine the me...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	3,055
2203.15410	Proximal-like algorithms for equilibrium seeking in mixed-integer Nash equilibrium problems	We consider potential games with mixed-integer variables, for which we propose two distributed, proximal-like equilibrium seeking algorithms. Specifically, we focus on two scenarios: i) the underlying game is generalized ordinal and the agents update through iterations by choosing an exact optimal strategy; ii) the gam...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	true	288,394
2103.00349	High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces	Bayesian optimization (BO) is a powerful paradigm for efficient optimization of black-box objective functions. High-dimensional BO presents a particular challenge, in part because the curse of dimensionality makes it difficult to define -- as well as do inference over -- a suitable class of surrogate models. We argue t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	222,236
2310.00041	Machine Learning Clifford invariants of ADE Coxeter elements	There has been recent interest in novel Clifford geometric invariants of linear transformations. This motivates the investigation of such invariants for a certain type of geometric transformation of interest in the context of root systems, reflection groups, Lie groups and Lie algebras: the Coxeter transformations. We ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	395,799
2304.13148	Introducing MBIB -- the first Media Bias Identification Benchmark Task and Dataset Collection	Although media bias detection is a complex multi-task problem, there is, to date, no unified benchmark grouping these evaluation tasks. We introduce the Media Bias Identification Benchmark (MBIB), a comprehensive benchmark that groups different types of media bias (e.g., linguistic, cognitive, political) under a common...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	360,474
2203.13799	Gravity-constrained point cloud registration	Visual and lidar Simultaneous Localization and Mapping (SLAM) algorithms benefit from the Inertial Measurement Unit (IMU) modality. The high-rate inertial data complement the other lower-rate modalities. Moreover, in the absence of constant acceleration, the gravity vector makes two attitude angles out of three observa...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	287,761
2301.06387	PECAN: Leveraging Policy Ensemble for Context-Aware Zero-Shot Human-AI Coordination	Zero-shot human-AI coordination holds the promise of collaborating with humans without human data. Prevailing methods try to train the ego agent with a population of partners via self-play. However, these methods suffer from two problems: 1) The diversity of a population with finite partners is limited, thereby limitin...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	340,631
2206.13511	Design and control analysis of a deployable clustered hyperbolic paraboloid cable net	This paper presents an analytical and experimental design and deployment control analysis of a hyperbolic paraboloid cable net based on clustering actuation strategies. First, the dynamics and statics for clustered tensegrity structures (CTS) are given. Then, we propose the topology design of the deployable hyperbolic ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	305,005
2202.06523	MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts	Understanding the performance of machine learning models across diverse data distributions is critically important for reliable applications. Motivated by this, there is a growing focus on curating benchmark datasets that capture distribution shifts. While valuable, the existing benchmarks are limited in that many of t...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	280,257
1605.05966	Dynamic Bayesian Networks to simulate occupant behaviours in office buildings related to indoor air quality	This paper proposes a new general approach based on Bayesian networks to model the human behaviour. This approach represents human behaviour with probabilistic cause-effect relations based on knowledge, but also with conditional probabilities coming either from knowledge or deduced from observations. This approach has ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	56,068
1806.08978	Inferring Metapopulation Propagation Network for Intra-city Epidemic Control and Prevention	Since the 21st century, the global outbreaks of infectious diseases such as SARS in 2003, H1N1 in 2009, and H7N9 in 2013, have become the critical threat to the public health and a hunting nightmare to the government. Understanding the propagation in large-scale metapopulations and predicting the future outbreaks thus ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	101,261
1904.06252	MAANet: Multi-view Aware Attention Networks for Image Super-Resolution	In most recent years, deep convolutional neural networks (DCNNs) based image super-resolution (SR) has gained increasing attention in multimedia and computer vision communities, focusing on restoring the high-resolution (HR) image from a low-resolution (LR) image. However, one nonnegligible flaw of DCNNs based methods ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	127,510
2010.06727	Joint Constrained Learning for Event-Event Relation Extraction	Understanding natural language involves recognizing how multiple event mentions structurally and temporally interact with each other. In this process, one can induce event complexes that organize multi-granular events with temporal order and membership relations interweaving among them. Due to the lack of jointly label...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	200,579
2403.00810	Bootstrapping Cognitive Agents with a Large Language Model	Large language models contain noisy general knowledge of the world, yet are hard to train or fine-tune. On the other hand cognitive architectures have excellent interpretability and are flexible to update but require a lot of manual work to instantiate. In this work, we combine the best of both worlds: bootstrapping a ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	434,121
2008.11719	A Three-Stage Algorithm for the Large Scale Dynamic Vehicle Routing Problem with an Industry 4.0 Approach	Companies are eager to have a smart supply chain especially when they have a dynamic system. Industry 4.0 is a concept which concentrates on mobility and real-time integration. Thus, it can be considered as a necessary component that has to be implemented for a Dynamic Vehicle Routing Problem. The aim of this research ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	193,360
2211.07415	MR-NOM: Multi-scale Resolution of Neuronal cells in Nissl-stained histological slices via deliberate Over-segmentation and Merging	In comparative neuroanatomy, the characterization of brain cytoarchitecture is critical to a better understanding of brain structure and function, as it helps to distill information on the development, evolution, and distinctive features of different populations. The automatic segmentation of individual brain cells is ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	330,239
2207.09531	LR-Net: A Block-based Convolutional Neural Network for Low-Resolution Image Classification	The success of CNN-based architecture on image classification in learning and extracting features made them so popular these days, but the task of image classification becomes more challenging when we apply state of art models to classify noisy and low-quality images. It is still difficult for models to extract meaning...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	308,923
2310.08446	Towards Robust Multi-Modal Reasoning via Model Selection	The reasoning capabilities of LLM (Large Language Model) are widely acknowledged in recent research, inspiring studies on tool learning and autonomous agents. LLM serves as the "brain" of the agent, orchestrating multiple tools for collaborative multi-step task solving. Unlike methods invoking tools like calculators or...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	399,396
1911.00714	Dynamic Ensemble Modeling Approach to Nonstationary Neural Decoding in Brain-Computer Interfaces	Brain-computer interfaces (BCIs) have enabled prosthetic device control by decoding motor movements from neural activities. Neural signals recorded from cortex exhibit nonstationary property due to abrupt noises and neuroplastic changes in brain activities during motor control. Current state-of-the-art neural signal de...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	151,898
2202.11878	New Benchmark for Household Garbage Image Recognition	Household garbage images are usually faced with complex backgrounds, variable illuminations, diverse angles, and changeable shapes, which bring a great difficulty in garbage image classification. Due to the ability to discover problem-specific features, deep learning and especially convolutional neural networks (CNNs) ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	282,031
2312.02665	Lights out: training RL agents robust to temporary blindness	Agents trained with DQN rely on an observation at each timestep to decide what action to take next. However, in real world applications observations can change or be missing entirely. Examples of this could be a light bulb breaking down, or the wallpaper in a certain room changing. While these situations change the act...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	412,966
2406.14295	Crowdfunding for Equitable EV Charging Infrastructure	The transportation sector significantly contributes to greenhouse gas emissions, highlighting the need to transition to Electric Vehicles (EVs) to reduce fossil fuel dependence and combat climate change. The US government has set ambitious targets for 2030, aiming for half of all new vehicles sold to be zero-emissions....	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	466,246
0811.3301	Faster Retrieval with a Two-Pass Dynamic-Time-Warping Lower Bound	The Dynamic Time Warping (DTW) is a popular similarity measure between time series. The DTW fails to satisfy the triangle inequality and its computation requires quadratic time. Hence, to find closest neighbors quickly, we use bounding techniques. We can avoid most DTW computations with an inexpensive lower bound (LB K...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	2,684
1911.11879	Schr\"odingeRNN: Generative Modeling of Raw Audio as a Continuously Observed Quantum State	We introduce Schr\"odingeRNN, a quantum inspired generative model for raw audio. Audio data is wave-like and is sampled from a continuous signal. Although generative modelling of raw audio has made great strides lately, relational inductive biases relevant to these two characteristics are mostly absent from models expl...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,244
2104.06473	Topology Estimation Following Islanding and its Impact on Preventive Control of Cascading Failure	Knowledge of power grid's topology during cascading failure is an essential element of centralized blackout prevention control, given that multiple islands are typically formed, as a cascade progresses. Moreover, academic research on interdependency between cyber and physical layers of the grid indicate that power fail...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	230,083
2405.20032	Promptus: Can Prompts Streaming Replace Video Streaming with Stable Diffusion	With the exponential growth of video traffic, traditional video streaming systems are approaching their limits in compression efficiency and communication capacity. To further reduce bitrate while maintaining quality, we propose Promptus, a disruptive novel system that streaming prompts instead of video content with St...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	459,167
2003.08559	Lifelong Learning with Searchable Extension Units	Lifelong learning remains an open problem. One of its main difficulties is catastrophic forgetting. Many dynamic expansion approaches have been proposed to address this problem, but they all use homogeneous models of predefined structure for all tasks. The common original model and expansion structures ignore the requi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	168,775
2402.17723	Seeing and Hearing: Open-domain Visual-Audio Generation with Diffusion Latent Aligners	Video and audio content creation serves as the core technique for the movie industry and professional users. Recently, existing diffusion-based methods tackle video and audio generation separately, which hinders the technique transfer from academia to industry. In this work, we aim at filling the gap, with a carefully ...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	433,115
2310.00229	Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning	Inspired by human conscious planning, we propose Skipper, a model-based reinforcement learning framework utilizing spatio-temporal abstractions to generalize better in novel situations. It automatically decomposes the given task into smaller, more manageable subtasks, and thus enables sparse decision-making and focused...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	395,881
2001.06448	Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification	The Information Bottleneck (IB) objective uses information theory to formulate a task-performance versus robustness trade-off. It has been successfully applied in the standard discriminative classification setting. We pose the question whether the IB can also be used to train generative likelihood models such as normal...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	160,802
1109.6726	A Fuzzy Co-Clustering approach for Clickstream Data Pattern	Web Usage mining is a very important tool to extract the hidden business intelligence data from large databases. The extracted information provides the organizations with the ability to produce results more effectively to improve their businesses and increasing of sales. Co-clustering is a powerful bipartition techniqu...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	12,410
1807.05618	Improved Person Re-Identification Based on Saliency and Semantic Parsing with Deep Neural Network Models	Given a video or an image of a person acquired from a camera, person re-identification is the process of retrieving all instances of the same person from videos or images taken from a different camera with non-overlapping view. This task has applications in various fields, such as surveillance, forensics, robotics, mul...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	102,960
cmp-lg/9806006	Dialogue Act Tagging with Transformation-Based Learning	For the task of recognizing dialogue acts, we are applying the Transformation-Based Learning (TBL) machine learning algorithm. To circumvent a sparse data problem, we extract values of well-motivated features of utterances, such as speaker direction, punctuation marks, and a new feature, called dialogue act cues, which...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,880
2012.02613	FinnSentiment -- A Finnish Social Media Corpus for Sentiment Polarity Annotation	Sentiment analysis and opinion mining is an important task with obvious application areas in social media, e.g. when indicating hate speech and fake news. In our survey of previous work, we note that there is no large-scale social media data set with sentiment polarity annotations for Finnish. This publications aims to...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	209,826
2202.10263	Strong Converse for Privacy Amplification against Quantum Side Information	We establish a one-shot strong converse bound for privacy amplification against quantum side information using trace distance as a security criterion. This strong converse bound implies that in the independent and identical scenario, the trace distance exponentially converges to one in every finite blocklength when the...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	281,473
2112.14381	COTReg:Coupled Optimal Transport based Point Cloud Registration	Generating a set of high-quality correspondences or matches is one of the most critical steps in point cloud registration. This paper proposes a learning framework COTReg by jointly considering the pointwise and structural matchings to predict correspondences of 3D point cloud registration. Specifically, we transform t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	273,513
1706.02509	Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2017)	The large scale of scholarly publications poses a challenge for scholars in information seeking and sensemaking. Bibliometrics, information retrieval (IR), text mining and NLP techniques could help in these search and look-up activities, but are not yet widely used. This workshop is intended to stimulate IR researchers...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	74,992
2304.05451	Performance Analysis of Centralized and Distributed Massive MIMO for MTC	Massive Multiple-Input Multiple-Output (mMIMO) is one of the essential technologies introduced by the Fifth Generation (5G) of wireless communication systems. However, although mMIMO provides many benefits for wireless communications, it cannot ensure uniform wireless coverage and suffers from inter-cell interference i...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	357,623
2104.05401	Adaptive conversion of real-valued input into spike trains	This paper presents a biologically plausible method for converting real-valued input into spike trains for processing with spiking neural networks. The proposed method mimics the adaptive behaviour of retinal ganglion cells and allows input neurons to adapt their response to changes in the statistics of the input. Thus...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	229,709
1504.08241	Explanation of Stagnation at Points that are not Local Optima in Particle Swarm Optimization by Potential Analysis	Particle Swarm Optimization (PSO) is a nature-inspired meta-heuristic for solving continuous optimization problems. In the literature, the potential of the particles of swarm has been used to show that slightly modified PSO guarantees convergence to local optima. Here we show that under specific circumstances the unmod...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	42,634

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