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
2112.13608	An Empirical Study of Adder Neural Networks for Object Detection	Adder neural networks (AdderNets) have shown impressive performance on image classification with only addition operations, which are more energy efficient than traditional convolutional neural networks built with multiplications. Compared with classification, there is a strong demand on reducing the energy consumption ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	273,306
2011.12799	StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation	We explore and analyze the latent style space of StyleGAN2, a state-of-the-art architecture for image generation, using models pretrained on several different datasets. We first show that StyleSpace, the space of channel-wise style parameters, is significantly more disentangled than the other intermediate latent spaces...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	208,271
2111.02717	Facial Emotion Recognition using Deep Residual Networks in Real-World Environments	Automatic affect recognition using visual cues is an important task towards a complete interaction between humans and machines. Applications can be found in tutoring systems and human computer interaction. A critical step towards that direction is facial feature extraction. In this paper, we propose a facial feature ex...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	264,954
2409.02335	What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits	A grand challenge in biology is to discover evolutionary traits - features of organisms common to a group of species with a shared ancestor in the tree of life (also referred to as phylogenetic tree). With the growing availability of image repositories in biology, there is a tremendous opportunity to discover evolution...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	485,654
2410.02284	Correlation and Navigation in the Vocabulary Key Representation Space of Language Models	Language model (LM) decoding is based on the next-token prediction (NTP) probability distribution. For neural LMs (e.g., Transformer-based), NTP distribution is essentially a softmax-regularized dot product between an encoded input context (query) and fixed vocabulary representations (keys). In this paper, we study the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	494,209
1703.03101	Robust MPC for tracking of nonholonomic robots with additive disturbances	In this paper, two robust model predictive control (MPC) schemes are proposed for tracking control of nonholonomic systems with bounded disturbances: tube-MPC and nominal robust MPC (NRMPC). In tube-MPC, the control signal consists of a control action and a nonlinear feedback law based on the deviation of the actual st...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	69,672
2410.23682	CubiXMusashi: Fusion of Wire-Driven CubiX and Musculoskeletal Humanoid Musashi toward Unlimited Performance	Humanoids exhibit a wide variety in terms of joint configuration, actuators, and degrees of freedom, resulting in different achievable movements and tasks for each type. Particularly, musculoskeletal humanoids are developed to closely emulate human body structure and movement functions, consisting of a skeletal framewo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	504,136
2408.01753	Opinion Dynamics with Set-Based Confidence: Convergence Criteria and Periodic Solutions	This paper introduces a new multidimensional extension of the Hegselmann-Krause (HK) opinion dynamics model, where opinion proximity is not determined by a norm or metric. Instead, each agent trusts opinions within the Minkowski sum $\xi+\mathcal{O}$, where $\xi$ is the agent's current opinion and $\mathcal{O}$ is the ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	478,365
1908.11645	EBPC: Extended Bit-Plane Compression for Deep Neural Network Inference and Training Accelerators	In the wake of the success of convolutional neural networks in image classification, object recognition, speech recognition, etc., the demand for deploying these compute-intensive ML models on embedded and mobile systems with tight power and energy constraints at low cost, as well as for boosting throughput in data cen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	143,435
2406.01304	CodeR: Issue Resolving with Multi-Agent and Task Graphs	GitHub issue resolving recently has attracted significant attention from academia and industry. SWE-bench is proposed to measure the performance in resolving issues. In this paper, we propose CodeR, which adopts a multi-agent framework and pre-defined task graphs to Repair & Resolve reported bugs and add new features w...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	460,258
2403.06716	Emergency Response Inference Mapping (ERIMap): A Bayesian Network-based Method for Dynamic Observation Processing in Spatially Distributed Emergencies	In emergencies, high stake decisions often have to be made under time pressure and strain. In order to support such decisions, information from various sources needs to be collected and processed rapidly. The information available tends to be temporally and spatially variable, uncertain, and sometimes conflicting, lead...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	436,572
2106.15433	Semantic Reasoning from Model-Agnostic Explanations	With the wide adoption of black-box models, instance-based \emph{post hoc} explanation tools, such as LIME and SHAP became increasingly popular. These tools produce explanations, pinpointing contributions of key features associated with a given prediction. However, the obtained explanations remain at the raw feature le...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	243,768
2305.03954	Learning Action Embeddings for Off-Policy Evaluation	Off-policy evaluation (OPE) methods allow us to compute the expected reward of a policy by using the logged data collected by a different policy. OPE is a viable alternative to running expensive online A/B tests: it can speed up the development of new policies, and reduces the risk of exposing customers to suboptimal t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	362,578
2101.11275	ASBSO: An Improved Brain Storm Optimization With Flexible Search Length and Memory-Based Selection	Brain storm optimization (BSO) is a newly proposed population-based optimization algorithm, which uses a logarithmic sigmoid transfer function to adjust its search range during the convergent process. However, this adjustment only varies with the current iteration number and lacks of flexibility and variety which makes...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	217,220
1301.4753	Pattern Matching for Self- Tuning of MapReduce Jobs	In this paper, we study CPU utilization time patterns of several MapReduce applications. After extracting running patterns of several applications, they are saved in a reference database to be later used to tweak system parameters to efficiently execute unknown applications in future. To achieve this goal, CPU utilizat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	21,274
1610.07418	Statistical Machine Translation for Indian Languages: Mission Hindi	This paper discusses Centre for Development of Advanced Computing Mumbai's (CDACM) submission to the NLP Tools Contest on Statistical Machine Translation in Indian Languages (ILSMT) 2014 (collocated with ICON 2014). The objective of the contest was to explore the effectiveness of Statistical Machine Translation (SMT) f...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	62,784
2003.10822	Pre-processing Image using Brightening, CLAHE and RETINEX	This paper focuses on finding the most optimal pre-processing methods considering three common algorithms for image enhancement: Brightening, CLAHE and Retinex. For the purpose of image training in general, these methods will be combined to find out the most optimal method for image enhancement. We have carried out the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	169,446
2109.04127	Word-Level Coreference Resolution	Recent coreference resolution models rely heavily on span representations to find coreference links between word spans. As the number of spans is $O(n^2)$ in the length of text and the number of potential links is $O(n^4)$, various pruning techniques are necessary to make this approach computationally feasible. We prop...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	254,289
2008.06640	Automatic Storage Structure Selection for hybrid Workload	In the use of database systems, the design of the storage engine and data model directly affects the performance of the database when performing queries. Therefore, the users of the database need to select the storage engine and design data model according to the workload encountered. However, in a hybrid workload, the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	191,848
2005.07930	HVS-Based Perceptual Color Compression of Image Data	In perceptual image coding applications, the main objective is to decrease, as much as possible, Bits Per Pixel (BPP) while avoiding noticeable distortions in the reconstructed image. In this paper, we propose a novel perceptual image coding technique, named Perceptual Color Compression (PCC). PCC is based on a novel m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	177,443
2005.02498	Plasticity without phenomenology: a first step	A novel, concurrent multiscale approach to meso/macroscale plasticity is demonstrated. It utilizes a carefully designed coupling of a partial differential equation (pde) based theory of dislocation mediated crystal plasticity with time-averaged inputs from microscopic Dislocation Dynamics (DD), adapting a state-of-the-...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	175,885
1903.04722	Progressive Generative Adversarial Binary Networks for Music Generation	Recent improvements in generative adversarial network (GAN) training techniques prove that progressively training a GAN drastically stabilizes the training and improves the quality of outputs produced. Adding layers after the previous ones have converged has proven to help in better overall convergence and stability of...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	124,034
2111.10769	Design of an Novel Spectrum Sensing Scheme Based on Long Short-Term Memory and Experimental Validation	Spectrum sensing allows cognitive radio systems to detect relevant signals in despite the presence of severe interference. Most of the existing spectrum sensing techniques use a particular signal-noise model with certain assumptions and derive certain detection performance. To deal with this uncertainty, learning based...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	267,439
2309.06420	Verifiable Reinforcement Learning Systems via Compositionality	We propose a framework for verifiable and compositional reinforcement learning (RL) in which a collection of RL subsystems, each of which learns to accomplish a separate subtask, are composed to achieve an overall task. The framework consists of a high-level model, represented as a parametric Markov decision process, w...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	391,413
1109.2415	Convergence Rates of Inexact Proximal-Gradient Methods for Convex Optimization	We consider the problem of optimizing the sum of a smooth convex function and a non-smooth convex function using proximal-gradient methods, where an error is present in the calculation of the gradient of the smooth term or in the proximity operator with respect to the non-smooth term. We show that both the basic proxim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	12,120
1211.0122	On Rational-Interpolation Based List-Decoding and List-Decoding Binary Goppa Codes	We derive the Wu list-decoding algorithm for Generalised Reed-Solomon (GRS) codes by using Gr\"obner bases over modules and the Euclidean algorithm (EA) as the initial algorithm instead of the Berlekamp-Massey algorithm (BMA). We present a novel method for constructing the interpolation polynomial fast. We give a new a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	19,510
1302.6330	An event-based model for contracts	We introduce a basic model for contracts. Our model extends event structures with a new relation, which faithfully captures the circular dependencies among contract clauses. We establish whether an agreement exists which respects all the contracts at hand (i.e. all the dependencies can be resolved), and we detect the o...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	22,369
1709.00657	Detection of Moving Object in Dynamic Background Using Gaussian Max-Pooling and Segmentation Constrained RPCA	Due to its efficiency and stability, Robust Principal Component Analysis (RPCA) has been emerging as a promising tool for moving object detection. Unfortunately, existing RPCA based methods assume static or quasi-static background, and thereby they may have trouble in coping with the background scenes that exhibit a pe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	79,944
1404.6369	Applying machine learning to the problem of choosing a heuristic to select the variable ordering for cylindrical algebraic decomposition	Cylindrical algebraic decomposition(CAD) is a key tool in computational algebraic geometry, particularly for quantifier elimination over real-closed fields. When using CAD, there is often a choice for the ordering placed on the variables. This can be important, with some problems infeasible with one variable ordering b...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	32,583
1912.12170	Mitigating large adversarial perturbations on X-MAS (X minus Moving Averaged Samples)	We propose the scheme that mitigates the adversarial perturbation $\epsilon$ on the adversarial example $X_{adv}$ ($=$ $X$ $\pm$ $\epsilon$, $X$ is a benign sample) by subtracting the estimated perturbation $\hat{\epsilon}$ from $X$ $+$ $\epsilon$ and adding $\hat{\epsilon}$ to $X$ $-$ $\epsilon$. The estimated perturb...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	158,785
1109.3798	Charge-Balanced Minimum-Power Controls for Spiking Neuron Oscillators	In this paper, we study the optimal control of phase models for spiking neuron oscillators. We focus on the design of minimum-power current stimuli that elicit spikes in neurons at desired times. We furthermore take the charge-balanced constraint into account because in practice undesirable side effects may occur due t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	12,213
2109.07471	Data-Driven Theory-guided Learning of Partial Differential Equations using SimultaNeous Basis Function Approximation and Parameter Estimation (SNAPE)	The measured spatiotemporal response of various physical processes is utilized to infer the governing partial differential equations (PDEs). We propose SimultaNeous Basis Function Approximation and Parameter Estimation (SNAPE), a technique of parameter estimation of PDEs that is robust against high levels of noise near...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	255,539
2007.14461	Modeling Behaviour to Predict User State: Self-Reports as Ground Truth	Methods that detect user states such as emotions are useful for interactive systems. In this position paper, we argue for model-based approaches that are trained on user behaviour and self-reported user state as ground truths. In an application context, they record behaviour, extract relevant features, and use the mode...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	189,400
cmp-lg/9601011	Parsing with Typed Feature Structures	In this paper we provide for parsing with respect to grammars expressed in a general TFS-based formalism, a restriction of ALE. Our motivation being the design of an abstract (WAM-like) machine for the formalism, we consider parsing as a computational process and use it as an operational semantics to guide the design o...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,492
1601.01607	NodIO, a JavaScript framework for volunteer-based evolutionary algorithms : first results	JavaScript is an interpreted language mainly known for its inclusion in web browsers, making them a container for rich Internet based applications. This has inspired its use, for a long time, as a tool for evolutionary algorithms, mainly so in browser-based volunteer computing environments. Several libraries have also ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	50,762
1910.03053	Graph Few-shot Learning via Knowledge Transfer	Towards the challenging problem of semi-supervised node classification, there have been extensive studies. As a frontier, Graph Neural Networks (GNNs) have aroused great interest recently, which update the representation of each node by aggregating information of its neighbors. However, most GNNs have shallow layers wi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	148,395
1603.03984	An efficient Exact-PGA algorithm for constant curvature manifolds	Manifold-valued datasets are widely encountered in many computer vision tasks. A non-linear analog of the PCA, called the Principal Geodesic Analysis (PGA) suited for data lying on Riemannian manifolds was reported in literature a decade ago. Since the objective function in PGA is highly non-linear and hard to solve ef...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	53,175
2101.00001	Etat de l'art sur l'application des bandits multi-bras	The Multi-armed bandit offer the advantage to learn and exploit the already learnt knowledge at the same time. This capability allows this approach to be applied in different domains, going from clinical trials where the goal is investigating the effects of different experimental treatments while minimizing patient los...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	213,933
2502.08512	Measuring Diversity in Synthetic Datasets	Large language models (LLMs) are widely adopted to generate synthetic datasets for various natural language processing (NLP) tasks, such as text classification and summarization. However, accurately measuring the diversity of these synthetic datasets-an aspect crucial for robust model performance-remains a significant ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	533,037
2303.02695	Understanding Bugs in Multi-Language Deep Learning Frameworks	Deep learning frameworks (DLFs) have been playing an increasingly important role in this intelligence age since they act as a basic infrastructure for an increasingly wide range of AIbased applications. Meanwhile, as multi-programming-language (MPL) software systems, DLFs are inevitably suffering from bugs caused by th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	349,454
2409.05006	HelmetPoser: A Helmet-Mounted IMU Dataset for Data-Driven Estimation of Human Head Motion in Diverse Conditions	Helmet-mounted wearable positioning systems are crucial for enhancing safety and facilitating coordination in industrial, construction, and emergency rescue environments. These systems, including LiDAR-Inertial Odometry (LIO) and Visual-Inertial Odometry (VIO), often face challenges in localization due to adverse envir...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	486,598
1801.00070	Sum of squares certificates for stability of planar, homogeneous, and switched systems	We show that existence of a global polynomial Lyapunov function for a homogeneous polynomial vector field or a planar polynomial vector field (under a mild condition) implies existence of a polynomial Lyapunov function that is a sum of squares (sos) and that the negative of its derivative is also a sum of squares. This...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	87,502
2205.10635	SplitPlace: AI Augmented Splitting and Placement of Large-Scale Neural Networks in Mobile Edge Environments	In recent years, deep learning models have become ubiquitous in industry and academia alike. Deep neural networks can solve some of the most complex pattern-recognition problems today, but come with the price of massive compute and memory requirements. This makes the problem of deploying such large-scale neural network...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	297,789
2306.17177	Leveraging ChatGPT As Text Annotation Tool For Sentiment Analysis	Sentiment analysis is a well-known natural language processing task that involves identifying the emotional tone or polarity of a given piece of text. With the growth of social media and other online platforms, sentiment analysis has become increasingly crucial for businesses and organizations seeking to monitor and co...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	376,620
2412.17282	LMD-PGN: Cross-Modal Knowledge Distillation from First-Person-View Images to Third-Person-View BEV Maps for Universal Point Goal Navigation	Point goal navigation (PGN) is a mapless navigation approach that trains robots to visually navigate to goal points without relying on pre-built maps. Despite significant progress in handling complex environments using deep reinforcement learning, current PGN methods are designed for single-robot systems, limiting thei...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	519,904
1809.07225	Deterministic limit of temporal difference reinforcement learning for stochastic games	Reinforcement learning in multiagent systems has been studied in the fields of economic game theory, artificial intelligence and statistical physics by developing an analytical understanding of the learning dynamics (often in relation to the replicator dynamics of evolutionary game theory). However, the majority of the...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	108,237
2105.05217	Representation Learning via Global Temporal Alignment and Cycle-Consistency	We introduce a weakly supervised method for representation learning based on aligning temporal sequences (e.g., videos) of the same process (e.g., human action). The main idea is to use the global temporal ordering of latent correspondences across sequence pairs as a supervisory signal. In particular, we propose a loss...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	234,750
2203.01668	Translational Lung Imaging Analysis Through Disentangled Representations	The development of new treatments often requires clinical trials with translational animal models using (pre)-clinical imaging to characterize inter-species pathological processes. Deep Learning (DL) models are commonly used to automate retrieving relevant information from the images. Nevertheless, they typically suffe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	283,473
1801.00444	Common Throughput Maximization in UAV-Enabled OFDMA Systems with Delay Consideration	The use of unmanned aerial vehicles (UAVs) as communication platforms is of great practical significance in future wireless networks, especially for on-demand deployment in temporary events and emergency situations. Although prior works have shown the performance improvement by exploiting the UAV's mobility, they mainl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	87,566
2308.13726	Dynamic Mode Decomposition for data-driven analysis and reduced-order modelling of ExB plasmas: I. Extraction of spatiotemporally coherent patterns	In this two-part article, we evaluate the utility and the generalizability of the Dynamic Mode Decomposition (DMD) algorithm for data-driven analysis and reduced-order modelling of plasma dynamics in cross-field ExB configurations. The DMD algorithm is an interpretable data-driven method that finds a best-fit linear mo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	388,026
2110.14196	From Image to Imuge: Immunized Image Generation	We introduce Imuge, an image tamper resilient generative scheme for image self-recovery. The traditional manner of concealing image content within the image are inflexible and fragile to diverse digital attack, i.e. image cropping and JPEG compression. To address this issue, we jointly train a U-Net backboned encoder, ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	263,456
2308.09599	Language-Guided Diffusion Model for Visual Grounding	Visual grounding (VG) tasks involve explicit cross-modal alignment, as semantically corresponding image regions are to be located for the language phrases provided. Existing approaches complete such visual-text reasoning in a single-step manner. Their performance causes high demands on large-scale anchors and over-desi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	386,354
2402.03289	Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS	Existing large language models (LLMs) for register transfer level code generation face challenges like compilation failures and suboptimal power, performance, and area (PPA) efficiency. This is due to the lack of PPA awareness in conventional transformer decoding algorithms. In response, we present an automated transfo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	426,941
2307.06401	Deterministic Multi-sensor Measurement-adaptive Birth using Labeled Random Finite Sets	Measurement-adaptive track initiation remains a critical design requirement of many practical multi-target tracking systems. For labeled random finite sets multi-object filters, prior work has been established to construct a labeled multi-object birth density using measurements from multiple sensors. A truncation proce...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	379,056
2105.04356	Coconut trees detection and segmentation in aerial imagery using mask region-based convolution neural network	Food resources face severe damages under extraordinary situations of catastrophes such as earthquakes, cyclones, and tsunamis. Under such scenarios, speedy assessment of food resources from agricultural land is critical as it supports aid activity in the disaster hit areas. In this article, a deep learning approach is ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	234,484
2206.05794	SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network	We investigate the inherent bias of Stochastic Gradient Descent (SGD) toward learning low-rank weight matrices during the training of deep neural networks. Our results demonstrate that training with mini-batch SGD and weight decay induces a bias toward rank minimization in the weight matrices. Specifically, we show bot...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,138
2309.01523	A Blackbox Model Is All You Need to Breach Privacy: Smart Grid Forecasting Models as a Use Case	This paper investigates the potential privacy risks associated with forecasting models, with specific emphasis on their application in the context of smart grids. While machine learning and deep learning algorithms offer valuable utility, concerns arise regarding their exposure of sensitive information. Previous studie...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	389,715
2111.11046	FRT-PAD: Effective Presentation Attack Detection Driven by Face Related Task	The robustness and generalization ability of Presentation Attack Detection (PAD) methods is critical to ensure the security of Face Recognition Systems (FRSs). However, in a real scenario, Presentation Attacks (PAs) are various and it is hard to predict the Presentation Attack Instrument (PAI) species that will be used...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	267,531
1703.08864	Learning Simpler Language Models with the Differential State Framework	Learning useful information across long time lags is a critical and difficult problem for temporal neural models in tasks such as language modeling. Existing architectures that address the issue are often complex and costly to train. The Differential State Framework (DSF) is a simple and high-performing design that uni...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	70,658
2308.05342	Metacognitive Prompting Improves Understanding in Large Language Models	In Large Language Models (LLMs), there have been consistent advancements in task-specific performance, largely influenced by effective prompt design. Recent advancements in prompting have enhanced reasoning in logic-intensive tasks for LLMs, yet the nuanced understanding abilities of these models, crucial for processin...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	384,755
1810.00818	RGB-D Object Detection and Semantic Segmentation for Autonomous Manipulation in Clutter	Autonomous robotic manipulation in clutter is challenging. A large variety of objects must be perceived in complex scenes, where they are partially occluded and embedded among many distractors, often in restricted spaces. To tackle these challenges, we developed a deep-learning approach that combines object detection a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	109,264
2005.12022	Learning to Charge RF-Energy Harvesting Devices in WiFi Networks	In this paper, we consider a solar-powered Access Point (AP) that is tasked with supporting both non-energy harvesting or legacy data users such as laptops, and devices with Radio Frequency (RF)-energy harvesting and sensing capabilities. We propose two solutions that enable the AP to manage its harvested energy via tr...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	178,625
2004.07085	Neural Status Registers	Standard Neural Networks can learn mathematical operations, but they do not extrapolate. Extrapolation means that the model can apply to larger numbers, well beyond those observed during training. Recent architectures tackle arithmetic operations and can extrapolate; however, the equally important problem of quantitati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	172,687
2403.11854	denoiSplit: a method for joint microscopy image splitting and unsupervised denoising	In this work, we present denoiSplit, a method to tackle a new analysis task, i.e. the challenge of joint semantic image splitting and unsupervised denoising. This dual approach has important applications in fluorescence microscopy, where semantic image splitting has important applications but noise does generally hinde...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	438,895
2006.07116	NAS-Bench-NLP: Neural Architecture Search Benchmark for Natural Language Processing	Neural Architecture Search (NAS) is a promising and rapidly evolving research area. Training a large number of neural networks requires an exceptional amount of computational power, which makes NAS unreachable for those researchers who have limited or no access to high-performance clusters and supercomputers. A few ben...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	181,693
1902.07580	Where Do Human Heuristics Come From?	Human decision-making deviates from the optimal solution, that maximizes cumulative rewards, in many situations. Here we approach this discrepancy from the perspective of bounded rationality and our goal is to provide a justification for such seemingly sub-optimal strategies. More specifically we investigate the hypoth...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	122,013
2408.01084	Adaptive Contrastive Decoding in Retrieval-Augmented Generation for Handling Noisy Contexts	When using large language models (LLMs) in knowledge-intensive tasks, such as open-domain question answering, external context can bridge the gap between external knowledge and the LLMs' parametric knowledge. Recent research has been developed to amplify contextual knowledge over the parametric knowledge of LLMs with c...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	478,096
2305.10467	Analysing Biomedical Knowledge Graphs using Prime Adjacency Matrices	Most phenomena related to biomedical tasks are inherently complex, and in many cases, are expressed as signals on biomedical Knowledge Graphs (KGs). In this work, we introduce the use of a new representation framework, the Prime Adjacency Matrix (PAM) for biomedical KGs, which allows for very efficient network analysis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	365,088
2502.05424	SAMGPT: Text-free Graph Foundation Model for Multi-domain Pre-training and Cross-domain Adaptation	Graphs are able to model interconnected entities in many online services, supporting a wide range of applications on the Web. This raises an important question: How can we train a graph foundational model on multiple source domains and adapt to an unseen target domain? A major obstacle is that graphs from different dom...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	531,598
2308.03570	Partial identification of kernel based two sample tests with mismeasured data	Nonparametric two-sample tests such as the Maximum Mean Discrepancy (MMD) are often used to detect differences between two distributions in machine learning applications. However, the majority of existing literature assumes that error-free samples from the two distributions of interest are available.We relax this assum...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	384,083
2209.04430	Investigation of a Machine learning methodology for the SKA pulsar search pipeline	The SKA pulsar search pipeline will be used for real time detection of pulsars. Modern radio telescopes such as SKA will be generating petabytes of data in their full scale of operation. Hence experience-based and data-driven algorithms become indispensable for applications such as candidate detection. Here we describe...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	316,783
2305.17873	The Digital Divide in Process Safety: Quantitative Risk Analysis of Human-AI Collaboration	Digital technologies have dramatically accelerated the digital transformation in process industries, boosted new industrial applications, upgraded the production system, and enhanced operational efficiency. In contrast, the challenges and gaps between human and artificial intelligence (AI) have become more and more pro...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	368,781
2406.19248	Staggered Quantizers for Perfect Perceptual Quality: A Connection between Quantizers with Common Randomness and Without	The rate-distortion-perception (RDP) framework has attracted significant recent attention due to its application in neural compression. It is important to understand the underlying mechanism connecting procedures with common randomness and those without. Different from previous efforts, we study this problem from a qua...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	468,349
2412.11744	Conditional Diffusion Models Based Conditional Independence Testing	Conditional independence (CI) testing is a fundamental task in modern statistics and machine learning. The conditional randomization test (CRT) was recently introduced to test whether two random variables, $X$ and $Y$, are conditionally independent given a potentially high-dimensional set of random variables, $Z$. The ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	517,561
1908.07902	Energy Management of Airport Service Electric Vehicles to Match Renewable Generation through Rollout Approach	Traditional diesel-based airport service vehicles are characterized by a heavy-duty, high-usage-frequency nature and a high carbon intensity per vehicle per hour. Transforming these vehicles into electric vehicles would reduce CO2 emissions and potentially save energy costs in the context of rising fuel prices, if a pr...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	142,412
2208.11484	An End-to-End OCR Framework for Robust Arabic-Handwriting Recognition using a Novel Transformers-based Model and an Innovative 270 Million-Words Multi-Font Corpus of Classical Arabic with Diacritics	This research is the second phase in a series of investigations on developing an Optical Character Recognition (OCR) of Arabic historical documents and examining how different modeling procedures interact with the problem. The first research studied the effect of Transformers on our custom-built Arabic dataset. One of ...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	314,444
2409.11474	A generalized non-hourglass updated Lagrangian formulation for SPH solid dynamics	Hourglass modes, characterized by zigzag particle and stress distributions, are a common numerical instability encountered when simulating solid materials with updated Lagrangian smoother particle hydrodynamics (ULSPH). While recent solutions have effectively addressed this issue in elastic materials using an essential...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	489,170
2310.01767	Differentially Encoded Observation Spaces for Perceptive Reinforcement Learning	Perceptive deep reinforcement learning (DRL) has lead to many recent breakthroughs for complex AI systems leveraging image-based input data. Applications of these results range from super-human level video game agents to dexterous, physically intelligent robots. However, training these perceptive DRL-enabled systems re...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	396,562
2407.13974	Continual Learning for Remote Physiological Measurement: Minimize Forgetting and Simplify Inference	Remote photoplethysmography (rPPG) has gained significant attention in recent years for its ability to extract physiological signals from facial videos. While existing rPPG measurement methods have shown satisfactory performance in intra-dataset and cross-dataset scenarios, they often overlook the incremental learning ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	474,587
2410.10756	Use Random Selection for Now: Investigation of Few-Shot Selection Strategies in LLM-based Text Augmentation for Classification	The generative large language models (LLMs) are increasingly used for data augmentation tasks, where text samples are paraphrased (or generated anew) and then used for classifier fine-tuning. Existing works on augmentation leverage the few-shot scenarios, where samples are given to LLMs as part of prompts, leading to b...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	498,214
1609.06261	Power-Domain Non-Orthogonal Multiple Access (NOMA) in 5G Systems: Potentials and Challenges	Non-orthogonal multiple access (NOMA) is one of the promising radio access techniques for performance enhancement in next-generation cellular communications. Compared to orthogonal frequency division multiple access (OFDMA), which is a well-known high-capacity orthogonal multiple access (OMA) technique, NOMA offers a s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	61,260
1809.00543	Learning Vision-based Cohesive Flight in Drone Swarms	This paper presents a data-driven approach to learning vision-based collective behavior from a simple flocking algorithm. We simulate a swarm of quadrotor drones and formulate the controller as a regression problem in which we generate 3D velocity commands directly from raw camera images. The dataset is created by simu...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	true	false	false	false	106,601
1311.1869	Optimization, Learning, and Games with Predictable Sequences	We provide several applications of Optimistic Mirror Descent, an online learning algorithm based on the idea of predictable sequences. First, we recover the Mirror Prox algorithm for offline optimization, prove an extension to Holder-smooth functions, and apply the results to saddle-point type problems. Next, we prove ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	28,261
2108.11845	Consistent Relative Confidence and Label-Free Model Selection for Convolutional Neural Networks	In this paper, we are concerned with image classification with deep convolutional neural networks (CNNs). We focus on the following question: given a set of candidate CNN models, how to select the right one with the best generalization property for the current task? Current model selection methods all require access to...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	252,313
2109.05375	From Instantaneous Schedulability to Worst Case Schedulability: A Significant Moment Approach	The method of significant moment analysis has been employed to derive instantaneous schedulability tests for real-time systems. However, the instantaneous schedulability can only be checked within a finite time window. On the other hand, worst-case schedulability guarantees schedulability of systems for infinite time. ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	254,767
2208.02070	Efficient Fine-Tuning of Compressed Language Models with Learners	Fine-tuning BERT-based models is resource-intensive in memory, computation, and time. While many prior works aim to improve inference efficiency via compression techniques, e.g., pruning, these works do not explicitly address the computational challenges of training to downstream tasks. We introduce Learner modules and...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	311,372
2104.03842	RNN Transducer Models For Spoken Language Understanding	We present a comprehensive study on building and adapting RNN transducer (RNN-T) models for spoken language understanding(SLU). These end-to-end (E2E) models are constructed in three practical settings: a case where verbatim transcripts are available, a constrained case where the only available annotations are SLU labe...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	229,192
1312.1683	Face Recognition using Hough Peaks extracted from the significant blocks of the Gradient Image	This paper proposes a new technique for automatic face recognition using integrated peaks of the Hough transformed significant blocks of the binary gradient image. In this approach firstly the gradient of an image is calculated and a threshold is set to obtain a binary gradient image, which is less sensitive to noise a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	28,876
2408.10599	Vision Calorimeter: Migrating Visual Object Detector to High-energy Particle Images	In high-energy physics, accurately estimating the kinematic parameters (position and momentum) of anti-neutrons ($\bar{n}$) is essential for exploring the fundamental governing principles. However, this process is particularly challenging when using an electromagnetic calorimeter (EMC) as the energy detector, due to th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	481,930
2209.08801	Sequence-to-Set Generative Models	In this paper, we propose a sequence-to-set method that can transform any sequence generative model based on maximum likelihood to a set generative model where we can evaluate the utility/probability of any set. An efficient importance sampling algorithm is devised to tackle the computational challenge of learning our ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	318,275
2206.14672	Not Cheating on the Turing Test: Towards Grounded Language Learning in Artificial Intelligence	Recent hype surrounding the increasing sophistication of language processing models has renewed optimism regarding machines achieving a human-like command of natural language. Research in the area of natural language understanding (NLU) in artificial intelligence claims to have been making great strides in this area, h...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	305,364
2012.12105	Warped Gaussian Processes in Remote Sensing Parameter Estimation and Causal Inference	This paper introduces warped Gaussian processes (WGP) regression in remote sensing applications. WGP models output observations as a parametric nonlinear transformation of a GP. The parameters of such prior model are then learned via standard maximum likelihood. We show the good performance of the proposed model for th...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	212,826
2106.10944	Hard hat wearing detection based on head keypoint localization	In recent years, a lot of attention is paid to deep learning methods in the context of vision-based construction site safety systems, especially regarding personal protective equipment. However, despite all this attention, there is still no reliable way to establish the relationship between workers and their hard hats....	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	242,223
2305.06162	Interpretable multimodal sentiment analysis based on textual modality descriptions by using large-scale language models	Multimodal sentiment analysis is an important area for understanding the user's internal states. Deep learning methods were effective, but the problem of poor interpretability has gradually gained attention. Previous works have attempted to use attention weights or vector distributions to provide interpretability. Howe...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	363,435
2303.02131	Spacetime-Efficient Low-Depth Quantum State Preparation with Applications	We propose a novel deterministic method for preparing arbitrary quantum states. When our protocol is compiled into CNOT and arbitrary single-qubit gates, it prepares an $N$-dimensional state in depth $O(\log(N))$ and spacetime allocation (a metric that accounts for the fact that oftentimes some ancilla qubits need not ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	349,230
2409.06961	Control Pneumatic Soft Bending Actuator with Feedforward Hysteresis Compensation by Pneumatic Physical Reservoir Computing	The nonlinearities of soft robots bring control challenges like hysteresis but also provide them with computational capacities. This paper introduces a fuzzy pneumatic physical reservoir computing (FPRC) model for feedforward hysteresis compensation in motion tracking control of soft actuators. Our method utilizes a pn...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	487,335
2411.17937	Spatio-temporal Causal Learning for Streamflow Forecasting	Streamflow plays an essential role in the sustainable planning and management of national water resources. Traditional hydrologic modeling approaches simulate streamflow by establishing connections across multiple physical processes, such as rainfall and runoff. These data, inherently connected both spatially and tempo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	511,662
1706.01443	Types of Cognition and its Implications for future High-Level Cognitive Machines	This work summarizes part of current knowledge on High-level Cognitive process and its relation with biological hardware. Thus, it is possible to identify some paradoxes which could impact the development of future technologies and artificial intelligence: we may make a High-level Cognitive Machine, sacrificing the pri...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	74,804
1812.08655	Surrogate-assisted Bayesian inversion for landscape and basin evolution models	The complex and computationally expensive nature of landscape evolution models pose significant challenges in the inference and optimisation of unknown parameters. Bayesian inference provides a methodology for estimation and uncertainty quantification of unknown model parameters. In our previous work, we developed para...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	true	117,026
1103.1124	Fluid flow analysis in a rough fracture (type II) using complex networks and lattice Boltzmann method	Complexity of fluid flow in a rough fracture is induced by the complex configurations of opening areas between the fracture planes. In this study, we model fluid flow in an evolvable real rock joint structure, which under certain normal load is sheared. In an experimental study, information regarding about apertures of...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	9,491

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