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
1605.09227	Learning Combinatorial Functions from Pairwise Comparisons	A large body of work in machine learning has focused on the problem of learning a close approximation to an underlying combinatorial function, given a small set of labeled examples. However, for real-valued functions, cardinal labels might not be accessible, or it may be difficult for an expert to consistently assign r...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	56,541
1905.01998	A Persona-based Multi-turn Conversation Model in an Adversarial Learning Framework	In this paper, we extend the persona-based sequence-to-sequence (Seq2Seq) neural network conversation model to multi-turn dialogue by modifying the state-of-the-art hredGAN architecture. To achieve this, we introduce an additional input modality into the encoder and decoder of hredGAN to capture other attributes such a...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	129,878
2112.01708	Emergency-braking Distance Prediction using Deep Learning	Predicting emergency-braking distance is important for the collision avoidance related features, which are the most essential and popular safety features for vehicles. In this study, we first gathered a large data set including a three-dimensional acceleration data and the corresponding emergency-braking distance. Usin...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	269,581
2208.02959	Towards No.1 in CLUE Semantic Matching Challenge: Pre-trained Language Model Erlangshen with Propensity-Corrected Loss	This report describes a pre-trained language model Erlangshen with propensity-corrected loss, the No.1 in CLUE Semantic Matching Challenge. In the pre-training stage, we construct a dynamic masking strategy based on knowledge in Masked Language Modeling (MLM) with whole word masking. Furthermore, by observing the speci...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	311,630
2412.08103	Multimodal Difference Learning for Sequential Recommendation	Sequential recommendations have drawn significant attention in modeling the user's historical behaviors to predict the next item. With the booming development of multimodal data (e.g., image, text) on internet platforms, sequential recommendation also benefits from the incorporation of multimodal data. Most methods int...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	515,941
2305.19775	Evolutionary Solution Adaption for Multi-Objective Metal Cutting Process Optimization	Optimizing manufacturing process parameters is typically a multi-objective problem with often contradictory objectives such as production quality and production time. If production requirements change, process parameters have to be optimized again. Since optimization usually requires costly simulations based on, for ex...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	369,683
1602.01208	Spatial Concept Acquisition for a Mobile Robot that Integrates Self-Localization and Unsupervised Word Discovery from Spoken Sentences	In this paper, we propose a novel unsupervised learning method for the lexical acquisition of words related to places visited by robots, from human continuous speech signals. We address the problem of learning novel words by a robot that has no prior knowledge of these words except for a primitive acoustic model. Furth...	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	51,676
1910.08841	Resilient Distributed Recovery of Large Fields	This paper studies the resilient distributed recovery of large fields under measurement attacks, by a team of agents, where each measures a small subset of the components of a large spatially distributed field. An adversary corrupts some of the measurements. The agents collaborate to process their measurements, and eac...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	149,986
1510.03495	Privacy Constrained Information Processing	This paper studies communication scenarios where the transmitter and the receiver have different objectives due to privacy concerns, in the context of a variation of the strategic information transfer (SIT) model of Sobel and Crawford. We first formulate the problem as the minimization of a common distortion by the tra...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	47,838
2402.14380	RadarMOSEVE: A Spatial-Temporal Transformer Network for Radar-Only Moving Object Segmentation and Ego-Velocity Estimation	Moving object segmentation (MOS) and Ego velocity estimation (EVE) are vital capabilities for mobile systems to achieve full autonomy. Several approaches have attempted to achieve MOSEVE using a LiDAR sensor. However, LiDAR sensors are typically expensive and susceptible to adverse weather conditions. Instead, millimet...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	431,655
2109.02069	New Communication Models and Decoding of Maximum Rank Distance Codes	In this paper an interpolation-based decoding algorithm to decode Gabidulin codes, transmitted through a finely restricted channel, is proposed. The algorithm is able to decode rank errors beyond half the minimum distance by one unit. Also the existing decoding algorithms for generalized twisted Gabidulin codes and add...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	253,622
2402.14905	MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases	This paper addresses the growing need for efficient large language models (LLMs) on mobile devices, driven by increasing cloud costs and latency concerns. We focus on designing top-quality LLMs with fewer than a billion parameters, a practical choice for mobile deployment. Contrary to prevailing belief emphasizing the ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	431,913
1406.6020	Stationary Mixing Bandits	We study the bandit problem where arms are associated with stationary phi-mixing processes and where rewards are therefore dependent: the question that arises from this setting is that of recovering some independence by ignoring the value of some rewards. As we shall see, the bandit problem we tackle requires us to add...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	34,082
2312.01898	Unlocking optimal batch size schedules using continuous-time control and perturbation theory	Stochastic Gradient Descent (SGD) and its variants are almost universally used to train neural networks and to fit a variety of other parametric models. An important hyperparameter in this context is the batch size, which determines how many samples are processed before an update of the parameters occurs. Previous stud...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	412,626
1802.01221	Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networks	Acquiring images of the same anatomy with multiple different contrasts increases the diversity of diagnostic information available in an MR exam. Yet, scan time limitations may prohibit acquisition of certain contrasts, and images for some contrast may be corrupted by noise and artifacts. In such cases, the ability to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,562
2411.04678	Socially-Aware Opinion-Based Navigation with Oval Limit Cycles	When humans move in a shared space, they choose navigation strategies that preserve their mutual safety. At the same time, each human seeks to minimise the number of modifications to her/his path. In order to achieve this result, humans use unwritten rules and reach a consensus on their decisions about the motion direc...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	506,365
2204.07123	Retrospective on the 2021 BASALT Competition on Learning from Human Feedback	We held the first-ever MineRL Benchmark for Agents that Solve Almost-Lifelike Tasks (MineRL BASALT) Competition at the Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021). The goal of the competition was to promote research towards agents that use learning from human feedback (LfHF) techniqu...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	291,570
1706.01805	SegAN: Adversarial Network with Multi-scale $L_1$ Loss for Medical Image Segmentation	Inspired by classic generative adversarial networks (GAN), we propose a novel end-to-end adversarial neural network, called SegAN, for the task of medical image segmentation. Since image segmentation requires dense, pixel-level labeling, the single scalar real/fake output of a classic GAN's discriminator may be ineffec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	74,868
1907.04246	Security for Distributed Deep Neural Networks Towards Data Confidentiality & Intellectual Property Protection	Current developments in Enterprise Systems observe a paradigm shift, moving the needle from the backend to the edge sectors of those; by distributing data, decentralizing applications and integrating novel components seamlessly to the central systems. Distributively deployed AI capabilities will thrust this transition....	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	138,061
2303.03187	Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting	Under stringent model type and variable distribution assumptions, differentiable score-based causal discovery methods learn a directed acyclic graph (DAG) from observational data by evaluating candidate graphs over an average score function. Despite great success in low-dimensional linear systems, it has been observed ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	349,637
2407.12329	Label-Efficient 3D Brain Segmentation via Complementary 2D Diffusion Models with Orthogonal Views	Deep learning-based segmentation techniques have shown remarkable performance in brain segmentation, yet their success hinges on the availability of extensive labeled training data. Acquiring such vast datasets, however, poses a significant challenge in many clinical applications. To address this issue, in this work, w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	473,873
1010.5806	Inner and Outer Bounds for the Gaussian Cognitive Interference Channel and New Capacity Results	The capacity of the Gaussian cognitive interference channel, a variation of the classical two-user interference channel where one of the transmitters (referred to as cognitive) has knowledge of both messages, is known in several parameter regimes but remains unknown in general. In this paper we provide a comparative ov...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,054
2107.12930	gaBERT -- an Irish Language Model	The BERT family of neural language models have become highly popular due to their ability to provide sequences of text with rich context-sensitive token encodings which are able to generalise well to many NLP tasks. We introduce gaBERT, a monolingual BERT model for the Irish language. We compare our gaBERT model to mul...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	248,050
1905.03894	Ship classification from overhead imagery using synthetic data and domain adaptation	In this paper, we revisit the problem of classifying ships (maritime vessels) detected from overhead imagery. Despite the last decade of research on this very important and pertinent problem, it remains largely unsolved. One of the major issues with the detection and classification of ships and other objects in the mar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	130,315
2311.03303	TS-Diffusion: Generating Highly Complex Time Series with Diffusion Models	While current generative models have achieved promising performances in time-series synthesis, they either make strong assumptions on the data format (e.g., regularities) or rely on pre-processing approaches (e.g., interpolations) to simplify the raw data. In this work, we consider a class of time series with three com...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	405,791
2010.15196	A fast and scalable computational framework for large-scale and high-dimensional Bayesian optimal experimental design	We develop a fast and scalable computational framework to solve large-scale and high-dimensional Bayesian optimal experimental design problems. In particular, we consider the problem of optimal observation sensor placement for Bayesian inference of high-dimensional parameters governed by partial differential equations ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	203,687
1409.5320	Potentials and Economics of Residential Thermal Loads Providing Regulation Reserve	Residential Thermostatically Controlled Loads (TCLs) such as Air Conditioners (ACs), heat pumps, water heaters, and refrigerators have an enormous thermal storage potential for providing regulation reserve to the grid. In this paper, we study the potential resource and economic analysis of TCLs providing frequency regu...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	36,157
1504.00057	Optimal Power Flow with Weighted Chance Constraints and General Policies for Generation Control	Due to the increasing amount of electricity generated from renewable sources, uncertainty in power system operation will grow. This has implications for tools such as Optimal Power Flow (OPF), an optimization problem widely used in power system operations and planning, which should be adjusted to account for this uncer...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	41,663
2401.02713	Graph-level Protein Representation Learning by Structure Knowledge Refinement	This paper focuses on learning representation on the whole graph level in an unsupervised manner. Learning graph-level representation plays an important role in a variety of real-world issues such as molecule property prediction, protein structure feature extraction, and social network analysis. The mainstream method i...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	419,820
2409.17330	VL4AD: Vision-Language Models Improve Pixel-wise Anomaly Detection	Semantic segmentation networks have achieved significant success under the assumption of independent and identically distributed data. However, these networks often struggle to detect anomalies from unknown semantic classes due to the limited set of visual concepts they are typically trained on. To address this issue, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	491,742
1702.06443	Phaseless Sampling and Reconstruction of Real-Valued Signals in Shift-Invariant Spaces	Sampling in shift-invariant spaces is a realistic model for signals with smooth spectrum. In this paper, we consider phaseless sampling and reconstruction of real-valued signals in a shift-invariant space from their magnitude measurements on the whole Euclidean space and from their phaseless samples taken on a discrete...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,610
2001.00804	Towards Intelligent Robotic Process Automation for BPMers	Robotic Process Automation (RPA) is a fast-emerging automation technology that sits between the fields of Business Process Management (BPM) and Artificial Intelligence (AI), and allows organizations to automate high volume routines. RPA tools are able to capture the execution of such routines previously performed by a ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	159,327
1410.5055	Prior Support Knowledge-Aided Sparse Bayesian Learning with Partly Erroneous Support Information	It has been shown both experimentally and theoretically that sparse signal recovery can be significantly improved given that part of the signal's support is known \emph{a priori}. In practice, however, such prior knowledge is usually inaccurate and contains errors. Using such knowledge may result in severe performance ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	36,862
1502.00137	Hybrid Radio/Free-Space Optical Design for Next Generation Backhaul Systems	The deluge of date rate in today's networks imposes a cost burden on the backhaul network design. Developing cost efficient backhaul solutions becomes an exciting, yet challenging, problem. Traditional technologies for backhaul networks include either radio-frequency backhauls (RF) or optical fibers (OF). While RF is a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,771
1402.1661	Network Sampling Based on NN Representatives	The amount of large-scale real data around us increase in size very quickly and so does the necessity to reduce its size by obtaining a representative sample. Such sample allows us to use a great variety of analytical methods, whose direct application on original data would be infeasible. There are many methods used fo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	30,692
1210.4875	A Theory of Goal-Oriented MDPs with Dead Ends	Stochastic Shortest Path (SSP) MDPs is a problem class widely studied in AI, especially in probabilistic planning. They describe a wide range of scenarios but make the restrictive assumption that the goal is reachable from any state, i.e., that dead-end states do not exist. Because of this, SSPs are unable to model var...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	19,200
2210.17217	AutoBag: Learning to Open Plastic Bags and Insert Objects	Thin plastic bags are ubiquitous in retail stores, healthcare, food handling, recycling, homes, and school lunchrooms. They are challenging both for perception (due to specularities and occlusions) and for manipulation (due to the dynamics of their 3D deformable structure). We formulate the task of "bagging:" manipulat...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	327,607
2501.01439	Probabilistic Mission Design in Neuro-Symbolic Systems	Advanced Air Mobility (AAM) is a growing field that demands accurate modeling of legal concepts and restrictions in navigating intelligent vehicles. In addition, any implementation of AAM needs to face the challenges posed by inherently dynamic and uncertain human-inhabited spaces robustly. Nevertheless, the employment...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	522,071
2205.00605	Cluster-based Regression using Variational Inference and Applications in Financial Forecasting	This paper describes an approach to simultaneously identify clusters and estimate cluster-specific regression parameters from the given data. Such an approach can be useful in learning the relationship between input and output when the regression parameters for estimating output are different in different regions of th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	294,313
2204.13637	Learning to Extract Building Footprints from Off-Nadir Aerial Images	Extracting building footprints from aerial images is essential for precise urban mapping with photogrammetric computer vision technologies. Existing approaches mainly assume that the roof and footprint of a building are well overlapped, which may not hold in off-nadir aerial images as there is often a big offset betwee...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,885
2007.11782	Accurate RGB-D Salient Object Detection via Collaborative Learning	Benefiting from the spatial cues embedded in depth images, recent progress on RGB-D saliency detection shows impressive ability on some challenge scenarios. However, there are still two limitations. One hand is that the pooling and upsampling operations in FCNs might cause blur object boundaries. On the other hand, usi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,638
2001.02330	High-Level Plan for Behavioral Robot Navigation with Natural Language Directions and R-NET	When the navigational environment is known, it can be represented as a graph where landmarks are nodes, the robot behaviors that move from node to node are edges, and the route is a set of behavioral instructions. The route path from source to destination can be viewed as a class of combinatorial optimization problems ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	159,707
2411.11777	Assistive Control of Knee Exoskeletons for Human Walking on Granular Terrains	Human walkers traverse diverse environments and demonstrate different gait locomotion and energy cost on granular terrains compared to solid ground. We present a stiffness-based model predictive control approach of knee exoskeleton assistance on sand. The gait and locomotion comparison is first discussed for human walk...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	509,171
1503.08237	Resource Allocation and Rate Gains in Practical Full-Duplex Systems	Full-duplex communication has the potential to substantially increase the throughput in wireless networks. However, the benefits of full-duplex are still not well understood. In this paper, we characterize the full-duplex rate gains in both single-channel and multi-channel use cases. For the single-channel case, we qua...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	41,561
1904.10754	OperatorNet: Recovering 3D Shapes From Difference Operators	This paper proposes a learning-based framework for reconstructing 3D shapes from functional operators, compactly encoded as small-sized matrices. To this end we introduce a novel neural architecture, called OperatorNet, which takes as input a set of linear operators representing a shape and produces its 3D embedding. W...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	128,700
2406.01359	R2C2-Coder: Enhancing and Benchmarking Real-world Repository-level Code Completion Abilities of Code Large Language Models	Code completion models have made significant progress in recent years. Recently, repository-level code completion has drawn more attention in modern software development, and several baseline methods and benchmarks have been proposed. However, existing repository-level code completion methods often fall short of fully ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	460,280
1909.07373	Policy Prediction Network: Model-Free Behavior Policy with Model-Based Learning in Continuous Action Space	This paper proposes a novel deep reinforcement learning architecture that was inspired by previous tree structured architectures which were only useable in discrete action spaces. Policy Prediction Network offers a way to improve sample complexity and performance on continuous control problems in exchange for extra com...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	145,652
1401.5858	SAP Speaks PDDL: Exploiting a Software-Engineering Model for Planning in Business Process Management	Planning is concerned with the automated solution of action sequencing problems described in declarative languages giving the action preconditions and effects. One important application area for such technology is the creation of new processes in Business Process Management (BPM), which is essential in an ever more dyn...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	30,258
1810.03051	Provable Subspace Tracking from Missing Data and Matrix Completion	We study the problem of subspace tracking in the presence of missing data (ST-miss). In recent work, we studied a related problem called robust ST. In this work, we show that a simple modification of our robust ST solution also provably solves ST-miss and robust ST-miss. To our knowledge, our result is the first `compl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	109,722
1901.10609	Deep Active Learning for Efficient Training of a LiDAR 3D Object Detector	Training a deep object detector for autonomous driving requires a huge amount of labeled data. While recording data via on-board sensors such as camera or LiDAR is relatively easy, annotating data is very tedious and time-consuming, especially when dealing with 3D LiDAR points or radar data. Active learning has the pot...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	120,060
2010.04617	Adaptive and Momentum Methods on Manifolds Through Trivializations	Adaptive methods do not have a direct generalization to manifolds as the adaptive term is not invariant. Momentum methods on manifolds suffer from efficiency problems stemming from the curvature of the manifold. We introduce a framework to generalize adaptive and momentum methods to arbitrary manifolds by noting that f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	199,809
2211.10515	Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments	Consider the problem of exploration in sparse-reward or reward-free environments, such as in Montezuma's Revenge. In the curiosity-driven paradigm, the agent is rewarded for how much each realized outcome differs from their predicted outcome. But using predictive error as intrinsic motivation is fragile in stochastic e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,329
1811.02872	Baselines for Reinforcement Learning in Text Games	The ability to learn optimal control policies in systems where action space is defined by sentences in natural language would allow many interesting real-world applications such as automatic optimisation of dialogue systems. Text-based games with multiple endings and rewards are a promising platform for this task, sinc...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	112,709
2412.16346	SOUS VIDE: Cooking Visual Drone Navigation Policies in a Gaussian Splatting Vacuum	We propose a new simulator, training approach, and policy architecture, collectively called SOUS VIDE, for end-to-end visual drone navigation. Our trained policies exhibit zero-shot sim-to-real transfer with robust real-world performance using only on-board perception and computation. Our simulator, called FiGS, couple...	false	false	false	false	false	false	true	true	false	false	true	true	false	false	false	false	false	false	519,475
2002.09917	Improve SGD Training via Aligning Mini-batches	Deep neural networks (DNNs) for supervised learning can be viewed as a pipeline of a feature extractor (i.e. last hidden layer) and a linear classifier (i.e. output layer) that is trained jointly with stochastic gradient descent (SGD). In each iteration of SGD, a mini-batch from the training data is sampled and the tru...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	165,228
2305.13191	Taxonomy Expansion for Named Entity Recognition	Training a Named Entity Recognition (NER) model often involves fixing a taxonomy of entity types. However, requirements evolve and we might need the NER model to recognize additional entity types. A simple approach is to re-annotate entire dataset with both existing and additional entity types and then train the model ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	366,391
2412.10741	RegMixMatch: Optimizing Mixup Utilization in Semi-Supervised Learning	Consistency regularization and pseudo-labeling have significantly advanced semi-supervised learning (SSL). Prior works have effectively employed Mixup for consistency regularization in SSL. However, our findings indicate that applying Mixup for consistency regularization may degrade SSL performance by compromising the ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	517,081
2003.08375	Pairwise Similarity Knowledge Transfer for Weakly Supervised Object Localization	Weakly Supervised Object Localization (WSOL) methods only require image level labels as opposed to expensive bounding box annotations required by fully supervised algorithms. We study the problem of learning localization model on target classes with weakly supervised image labels, helped by a fully annotated source dat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	168,718
2406.12632	Cyclic 2.5D Perceptual Loss for Cross-Modal 3D Image Synthesis: T1 MRI to Tau-PET	Alzheimer's Disease (AD) is the most common form of dementia, characterised by cognitive decline and biomarkers such as tau-proteins. Tau-positron emission tomography (tau-PET), which employs a radiotracer to selectively bind, detect, and visualise tau protein aggregates within the brain, is valuable for early AD diagn...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	465,497
2501.15038	Adaptive Client Selection in Federated Learning: A Network Anomaly Detection Use Case	Federated Learning (FL) has become a widely used approach for training machine learning models on decentralized data, addressing the significant privacy concerns associated with traditional centralized methods. However, the efficiency of FL relies on effective client selection and robust privacy preservation mechanisms...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	527,368
2410.05356	BSG4Bot: Efficient Bot Detection based on Biased Heterogeneous Subgraphs	The detection of malicious social bots has become a crucial task, as bots can be easily deployed and manipulated to spread disinformation, promote conspiracy messages, and more. Most existing approaches utilize graph neural networks (GNNs)to capture both user profle and structural features,achieving promising progress....	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	495,702
2103.05333	Control Design with Guaranteed Transient Performance: an Approach with Polyhedral Target Tubes	In this paper a novel approach is presented for control design with guaranteed transient performance for multiple-input multiple-output discrete-time linear polytopic difference inclusions. We establish a theorem that gives necessary and sufficient conditions for the state to evolve from one polyhedral subset of the st...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	223,944
2206.03936	Linear Precoder Design in Massive MIMO under Realistic Power Amplifier Consumption Constraint	The energy consumption of wireless networks is a growing concern. In massive MIMO systems, which are being increasingly deployed as part of the 5G roll-out, the power amplifiers in the base stations have a large impact in terms of power demands. Most of the current massive MIMO precoders are designed to minimize the tr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	301,458
2303.09757	Video Dehazing via a Multi-Range Temporal Alignment Network with Physical Prior	Video dehazing aims to recover haze-free frames with high visibility and contrast. This paper presents a novel framework to effectively explore the physical haze priors and aggregate temporal information. Specifically, we design a memory-based physical prior guidance module to encode the prior-related features into lon...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,175
2211.13802	Sequential Gradient Coding For Straggler Mitigation	In distributed computing, slower nodes (stragglers) usually become a bottleneck. Gradient Coding (GC), introduced by Tandon et al., is an efficient technique that uses principles of error-correcting codes to distribute gradient computation in the presence of stragglers. In this paper, we consider the distributed comput...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	332,602
1908.00380	Optimization-based Control for Bearing-only Target Search with a Mobile Vehicle	This work aims to design an optimization-based controller for a discrete-time Dubins vehicle to approach a target with unknown position as fast as possible by only using bearing measurements. To this end, we propose a bi-objective optimization problem, which jointly considers the performance of estimating the unknown t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	140,498
2308.02501	Transactional Indexes on (RDMA or CXL-based) Disaggregated Memory with Repairable Transaction	The failure atomic and isolated execution of clients operations is a default requirement for a system that serve multiple loosely coupled clients at a server. However, disaggregated memory breaks this requirement in remote indexes because a client operation is disaggregated to multiple remote reads/writes. Current inde...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	383,648
1005.5035	Dynamic Motion Modelling for Legged Robots	An accurate motion model is an important component in modern-day robotic systems, but building such a model for a complex system often requires an appreciable amount of manual effort. In this paper we present a motion model representation, the Dynamic Gaussian Mixture Model (DGMM), that alleviates the need to manually ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	6,582
2109.05746	ChangeChip: A Reference-Based Unsupervised Change Detection for PCB Defect Detection	The usage of electronic devices increases, and becomes predominant in most aspects of life. Surface Mount Technology (SMT) is the most common industrial method for manufacturing electric devices in which electrical components are mounted directly onto the surface of a Printed Circuit Board (PCB). Although the expansion...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	254,924
1408.5518	Faster construction of asymptotically good unit-cost error correcting codes in the RAM model	Assuming we are in a Word-RAM model with word size $w$, we show that we can construct in $o(w)$ time an error correcting code with a constant relative positive distance that maps numbers of $w$ bits into $\Theta(w)$-bit numbers, and such that the application of the error-correcting code on any given number $x\in[0,2^w-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	35,557
2303.08027	A Hierarchical Regression Chain Framework for Affective Vocal Burst Recognition	As a common way of emotion signaling via non-linguistic vocalizations, vocal burst (VB) plays an important role in daily social interaction. Understanding and modeling human vocal bursts are indispensable for developing robust and general artificial intelligence. Exploring computational approaches for understanding voc...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	351,476
2211.06738	Formalizing the presumption of independence	Mathematical proof aims to deliver confident conclusions, but a very similar process of deduction can be used to make uncertain estimates that are open to revision. A key ingredient in such reasoning is the use of a "default" estimate of $\mathbb{E}[XY] = \mathbb{E}[X] \mathbb{E}[Y]$ in the absence of any specific info...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	330,002
2012.08009	Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning	Due to communication constraints and intermittent client availability in federated learning, only a subset of clients can participate in each training round. While most prior works assume uniform and unbiased client selection, recent work on biased client selection has shown that selecting clients with higher local los...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	211,625
2111.03089	Measuring Proximity in Attributed Networks for Community Detection	Proximity measures on graphs have a variety of applications in network analysis, including community detection. Previously they have been mainly studied in the context of networks without attributes. If node attributes are taken into account, however, this can provide more insight into the network structure. In this pa...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	265,048
2402.04417	Decentralized Blockchain-based Robust Multi-agent Multi-armed Bandit	We study a robust, i.e. in presence of malicious participants, multi-agent multi-armed bandit problem where multiple participants are distributed on a fully decentralized blockchain, with the possibility of some being malicious. The rewards of arms are homogeneous among the honest participants, following time-invariant...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	427,440
2209.02022	How Much User Context Do We Need? Privacy by Design in Mental Health NLP Application	Clinical NLP tasks such as mental health assessment from text, must take social constraints into account - the performance maximization must be constrained by the utmost importance of guaranteeing privacy of user data. Consumer protection regulations, such as GDPR, generally handle privacy by restricting data availabil...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	316,079
2303.08541	Adapting U-Net for linear elastic stress estimation in polycrystal Zr microstructures	A variant of the U-Net convolutional neural network architecture is proposed to estimate linear elastic compatibility stresses in a-Zr (hcp) polycrystalline grain structures. Training data was generated using VGrain software with a regularity alpha of 0.73 and uniform random orientation for the grain structures and ABA...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	351,683
2301.09620	Tracking the industrial growth of modern China with high-resolution panchromatic imagery: A sequential convolutional approach	Due to insufficient or difficult to obtain data on development in inaccessible regions, remote sensing data is an important tool for interested stakeholders to collect information on economic growth. To date, no studies have utilized deep learning to estimate industrial growth at the level of individual sites. In this ...	false	false	false	false	false	false	true	false	false	false	false	true	false	true	false	false	false	false	341,549
2311.02576	Towards Feasible Dynamic Grasping: Leveraging Gaussian Process Distance Field, SE(3) Equivariance and Riemannian Mixture Models	This paper introduces a novel approach to improve robotic grasping in dynamic environments by integrating Gaussian Process Distance Fields (GPDF), SE(3) equivariant networks, and Riemannian Mixture Models. The aim is to enable robots to grasp moving objects effectively. Our approach comprises three main components: obj...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	405,500
1706.08107	Detekcja upadku i wybranych akcji na sekwencjach obraz\'ow cyfrowych	In recent years a growing interest on action recognition is observed, including detection of fall accident for the elderly. However, despite many efforts undertaken, the existing technology is not widely used by elderly, mainly because of its flaws like low precision, large number of false alarms, inadequate privacy pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	75,945
2112.06334	DPICT: Deep Progressive Image Compression Using Trit-Planes	We propose the deep progressive image compression using trit-planes (DPICT) algorithm, which is the first learning-based codec supporting fine granular scalability (FGS). First, we transform an image into a latent tensor using an analysis network. Then, we represent the latent tensor in ternary digits (trits) and encod...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	271,135
2412.17596	LiveIdeaBench: Evaluating LLMs' Scientific Creativity and Idea Generation with Minimal Context	While Large Language Models (LLMs) have demonstrated remarkable capabilities in scientific tasks, existing evaluation frameworks primarily assess their performance using rich contextual inputs, overlooking their ability to generate novel ideas from minimal information. We introduce LiveIdeaBench, a comprehensive benchm...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	520,043
1704.02781	Tracking the Trackers: An Analysis of the State of the Art in Multiple Object Tracking	Standardized benchmarks are crucial for the majority of computer vision applications. Although leaderboards and ranking tables should not be over-claimed, benchmarks often provide the most objective measure of performance and are therefore important guides for research. We present a benchmark for Multiple Object Tracki...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	71,508
2006.06376	Wide and Deep Graph Neural Networks with Distributed Online Learning	Graph neural networks (GNNs) learn representations from network data with naturally distributed architectures, rendering them well-suited candidates for decentralized learning. Oftentimes, this decentralized graph support changes with time due to link failures or topology variations. These changes create a mismatch bet...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,409
1910.01843	Prediction of Human Full-Body Movements with Motion Optimization and Recurrent Neural Networks	Human movement prediction is difficult as humans naturally exhibit complex behaviors that can change drastically from one environment to the next. In order to alleviate this issue, we propose a prediction framework that decouples short-term prediction, linked to internal body dynamics, and long-term prediction, linked ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	148,053
2408.14769	Points2Plans: From Point Clouds to Long-Horizon Plans with Composable Relational Dynamics	We present Points2Plans, a framework for composable planning with a relational dynamics model that enables robots to solve long-horizon manipulation tasks from partial-view point clouds. Given a language instruction and a point cloud of the scene, our framework initiates a hierarchical planning procedure, whereby a lan...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	483,665
2206.08464	PRANC: Pseudo RAndom Networks for Compacting deep models	We demonstrate that a deep model can be reparametrized as a linear combination of several randomly initialized and frozen deep models in the weight space. During training, we seek local minima that reside within the subspace spanned by these random models (i.e., `basis' networks). Our framework, PRANC, enables signific...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	303,148
2303.08594	FastInst: A Simple Query-Based Model for Real-Time Instance Segmentation	Recent attention in instance segmentation has focused on query-based models. Despite being non-maximum suppression (NMS)-free and end-to-end, the superiority of these models on high-accuracy real-time benchmarks has not been well demonstrated. In this paper, we show the strong potential of query-based models on efficie...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,703
1811.02840	Neural Image Compression for Gigapixel Histopathology Image Analysis	We propose Neural Image Compression (NIC), a two-step method to build convolutional neural networks for gigapixel image analysis solely using weak image-level labels. First, gigapixel images are compressed using a neural network trained in an unsupervised fashion, retaining high-level information while suppressing pixe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	112,703
2312.02037	GFS: Graph-based Feature Synthesis for Prediction over Relational Databases	Relational databases are extensively utilized in a variety of modern information system applications, and they always carry valuable data patterns. There are a huge number of data mining or machine learning tasks conducted on relational databases. However, it is worth noting that there are limited machine learning mode...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	412,670
1908.01927	Distributed Stability Conditions for Power Systems with Heterogeneous Nonlinear Bus Dynamics	This paper derives distributed conditions that guarantee the system-wide stability for power systems with nonlinear and heterogeneous bus dynamics interconnected via power network. Our conditions require each bus dynamics should satisfy certain passivity-like conditions with a large enough passivity index, a sufficient...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	140,887
2305.04080	Robust Tensor CUR Decompositions: Rapid Low-Tucker-Rank Tensor Recovery with Sparse Corruption	We study the tensor robust principal component analysis (TRPCA) problem, a tensorial extension of matrix robust principal component analysis (RPCA), that aims to split the given tensor into an underlying low-rank component and a sparse outlier component. This work proposes a fast algorithm, called Robust Tensor CUR Dec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	362,625
2405.20323	$\textit{S}^3$Gaussian: Self-Supervised Street Gaussians for Autonomous Driving	Photorealistic 3D reconstruction of street scenes is a critical technique for developing real-world simulators for autonomous driving. Despite the efficacy of Neural Radiance Fields (NeRF) for driving scenes, 3D Gaussian Splatting (3DGS) emerges as a promising direction due to its faster speed and more explicit represe...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	459,291
2103.06999	An Efficient Hypergraph Approach to Robust Point Cloud Resampling	Efficient processing and feature extraction of largescale point clouds are important in related computer vision and cyber-physical systems. This work investigates point cloud resampling based on hypergraph signal processing (HGSP) to better explore the underlying relationship among different cloud points and to extract...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	224,462
1909.13062	Implicit Discriminator in Variational Autoencoder	Recently generative models have focused on combining the advantages of variational autoencoders (VAE) and generative adversarial networks (GAN) for good reconstruction and generative abilities. In this work we introduce a novel hybrid architecture, Implicit Discriminator in Variational Autoencoder (IDVAE), that combine...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	147,315
2502.14708	Human Misperception of Generative-AI Alignment: A Laboratory Experiment	We conduct an incentivized laboratory experiment to study people's perception of generative artificial intelligence (GenAI) alignment in the context of economic decision-making. Using a panel of economic problems spanning the domains of risk, time preference, social preference, and strategic interactions, we ask human ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	535,935
2205.03971	Private Eye: On the Limits of Textual Screen Peeking via Eyeglass Reflections in Video Conferencing	Using mathematical modeling and human subjects experiments, this research explores the extent to which emerging webcams might leak recognizable textual and graphical information gleaming from eyeglass reflections captured by webcams. The primary goal of our work is to measure, compute, and predict the factors, limits, ...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	295,484
1908.01612	Multi-Contrast Super-Resolution MRI Through a Progressive Network	Magnetic resonance imaging (MRI) is widely used for screening, diagnosis, image-guided therapy, and scientific research. A significant advantage of MRI over other imaging modalities such as computed tomography (CT) and nuclear imaging is that it clearly shows soft tissues in multi-contrasts. Compared with other medical...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	140,806
2407.16482	BONES: a Benchmark fOr Neural Estimation of Shapley values	Shapley Values are concepts established for eXplainable AI. They are used to explain black-box predictive models by quantifying the features' contributions to the model's outcomes. Since computing the exact Shapley Values is known to be computationally intractable on real-world datasets, neural estimators have emerged ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	475,617
1607.05396	Binary Hashing with Semidefinite Relaxation and Augmented Lagrangian	This paper proposes two approaches for inferencing binary codes in two-step (supervised, unsupervised) hashing. We first introduce an unified formulation for both supervised and unsupervised hashing. Then, we cast the learning of one bit as a Binary Quadratic Problem (BQP). We propose two approaches to solve BQP. In th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	58,746

Subsets and Splits

No community queries yet

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