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
2405.11935	A Flat Dual-Polarized Millimeter-Wave Luneburg Lens Antenna Using Transformation Optics with Reduced Anisotropy and Impedance Mismatch	In this paper, a compact wideband dual-polarized Luneburg lens antenna (LLA) with reduced anisotropy and improved impedance matching is proposed in Ka band with a wide 2D beamscanning capability. Based on transformation optics, the spherical Luneburg lens is compressed into a cylindrical one, while the merits of high g...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	455,350
1602.01061	Waveform Optimization for SWIPT with Nonlinear Energy Harvester Modeling	Simultaneous Wireless Information and Power Transfer (SWIPT) has attracted significant attention in the communication community. The problem of waveform design for SWIPT has however never been addressed so far. In this paper, a novel SWIPT transceiver architecture is introduced relying on the superposition of multisine...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	51,656
2101.04097	Correlated Weights in Infinite Limits of Deep Convolutional Neural Networks	Infinite width limits of deep neural networks often have tractable forms. They have been used to analyse the behaviour of finite networks, as well as being useful methods in their own right. When investigating infinitely wide convolutional neural networks (CNNs), it was observed that the correlations arising from spati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	215,066
2209.11302	ProgPrompt: Generating Situated Robot Task Plans using Large Language Models	Task planning can require defining myriad domain knowledge about the world in which a robot needs to act. To ameliorate that effort, large language models (LLMs) can be used to score potential next actions during task planning, and even generate action sequences directly, given an instruction in natural language with n...	false	false	false	false	true	false	true	true	true	false	false	false	false	false	false	false	false	false	319,139
1204.4107	Towards the Evolution of Vertical-Axis Wind Turbines using Supershapes	We have recently presented an initial study of evolutionary algorithms used to design vertical-axis wind turbines (VAWTs) wherein candidate prototypes are evaluated under approximated wind tunnel conditions after being physically instantiated by a 3D printer. That is, unlike other approaches such as computational fluid...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	15,565
1911.07983	Task-Based Hybrid Shared Control for Training Through Forceful Interaction	Despite the fact that robotic platforms can provide both consistent practice and objective assessments of users over the course of their training, there are relatively few instances where physical human robot interaction has been significantly more effective than unassisted practice or human-mediated training. This pap...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	154,042
1905.11067	Locally Differentially Private Minimum Finding	We investigate a problem of finding the minimum, in which each user has a real value and we want to estimate the minimum of these values under the local differential privacy constraint. We reveal that this problem is fundamentally difficult, and we cannot construct a mechanism that is consistent in the worst case. Inst...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	132,321
2205.12183	StylizedNeRF: Consistent 3D Scene Stylization as Stylized NeRF via 2D-3D Mutual Learning	3D scene stylization aims at generating stylized images of the scene from arbitrary novel views following a given set of style examples, while ensuring consistency when rendered from different views. Directly applying methods for image or video stylization to 3D scenes cannot achieve such consistency. Thanks to recentl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	298,432
1703.01423	Soft Pneumatic Gelatin Actuator for Edible Robotics	We present a fully edible pneumatic actuator based on gelatin-glycerol composite. The actuator is monolithic, fabricated via a molding process, and measures 90 mm in length, 20 mm in width, and 17 mm in thickness. Thanks to the composite mechanical characteristics similar to those of silicone elastomers, the actuator e...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	69,360
1110.5015	Spectral descriptors for deformable shapes	Informative and discriminative feature descriptors play a fundamental role in deformable shape analysis. For example, they have been successfully employed in correspondence, registration, and retrieval tasks. In the recent years, significant attention has been devoted to descriptors obtained from the spectral decomposi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	12,741
2310.03392	Unpacking Human-AI Interaction in Safety-Critical Industries: A Systematic Literature Review	Ensuring quality human-AI interaction (HAII) in safety-critical industries is essential. Failure to do so can lead to catastrophic and deadly consequences. Despite this urgency, existing research on HAII is limited, fragmented, and inconsistent. We present here a survey of that literature and recommendations for resear...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	397,268
1803.03684	Scoring Formulation for Multi-Condition Joint PLDA	The joint PLDA model, is a generalization of PLDA where the nuisance variable is no longer considered independent across samples, but potentially shared (tied) across samples that correspond to the same nuisance condition. The original work considered a single nuisance condition, deriving the EM and scoring formulas fo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	92,297
0811.0134	A Novel Parser Design Algorithm Based on Artificial Ants	This article presents a unique design for a parser using the Ant Colony Optimization algorithm. The paper implements the intuitive thought process of human mind through the activities of artificial ants. The scheme presented here uses a bottom-up approach and the parsing program can directly use ambiguous or redundant ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	2,598
2402.08493	Sparsity via Sparse Group $k$-max Regularization	For the linear inverse problem with sparsity constraints, the $l_0$ regularized problem is NP-hard, and existing approaches either utilize greedy algorithms to find almost-optimal solutions or to approximate the $l_0$ regularization with its convex counterparts. In this paper, we propose a novel and concise regularizat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	429,118
2311.00444	Form follows Function: Text-to-Text Conditional Graph Generation based on Functional Requirements	This work focuses on the novel problem setting of generating graphs conditioned on a description of the graph's functional requirements in a downstream task. We pose the problem as a text-to-text generation problem and focus on the approach of fine-tuning a pretrained large language model (LLM) to generate graphs. We p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	404,655
2408.08088	KGV: Integrating Large Language Models with Knowledge Graphs for Cyber Threat Intelligence Credibility Assessment	Cyber threat intelligence is a critical tool that many organizations and individuals use to protect themselves from sophisticated, organized, persistent, and weaponized cyber attacks. However, few studies have focused on the quality assessment of threat intelligence provided by intelligence platforms, and this work sti...	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	480,853
2008.09566	Differentiable TAN Structure Learning for Bayesian Network Classifiers	Learning the structure of Bayesian networks is a difficult combinatorial optimization problem. In this paper, we consider learning of tree-augmented naive Bayes (TAN) structures for Bayesian network classifiers with discrete input features. Instead of performing a combinatorial optimization over the space of possible g...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	192,751
2212.04559	SpeechLMScore: Evaluating speech generation using speech language model	While human evaluation is the most reliable metric for evaluating speech generation systems, it is generally costly and time-consuming. Previous studies on automatic speech quality assessment address the problem by predicting human evaluation scores with machine learning models. However, they rely on supervised learnin...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	335,482
2201.05371	Artificial Intelligence in Software Testing : Impact, Problems, Challenges and Prospect	Artificial Intelligence (AI) is making a significant impact in multiple areas like medical, military, industrial, domestic, law, arts as AI is capable to perform several roles such as managing smart factories, driving autonomous vehicles, creating accurate weather forecasts, detecting cancer and personal assistants, et...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	275,373
2105.11113	Dynamic Class Queue for Large Scale Face Recognition In the Wild	Learning discriminative representation using large-scale face datasets in the wild is crucial for real-world applications, yet it remains challenging. The difficulties lie in many aspects and this work focus on computing resource constraint and long-tailed class distribution. Recently, classification-based representati...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	236,600
1904.05878	Knowledge Flow: Improve Upon Your Teachers	A zoo of deep nets is available these days for almost any given task, and it is increasingly unclear which net to start with when addressing a new task, or which net to use as an initialization for fine-tuning a new model. To address this issue, in this paper, we develop knowledge flow which moves 'knowledge' from mult...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	127,430
2108.04927	Embodied BERT: A Transformer Model for Embodied, Language-guided Visual Task Completion	Language-guided robots performing home and office tasks must navigate in and interact with the world. Grounding language instructions against visual observations and actions to take in an environment is an open challenge. We present Embodied BERT (EmBERT), a transformer-based model which can attend to high-dimensional,...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	250,152
1709.05437	A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects	Tracking humans that are interacting with the other subjects or environment remains unsolved in visual tracking, because the visibility of the human of interests in videos is unknown and might vary over time. In particular, it is still difficult for state-of-the-art human trackers to recover complete human trajectories...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	80,868
1212.0220	Metaheuristic Optimization: Algorithm Analysis and Open Problems	Metaheuristic algorithms are becoming an important part of modern optimization. A wide range of metaheuristic algorithms have emerged over the last two decades, and many metaheuristics such as particle swarm optimization are becoming increasingly popular. Despite their popularity, mathematical analysis of these algorit...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	20,077
0905.3030	Performance of Cognitive Radio Systems with Imperfect Radio Environment Map Information	In this paper we describe the effect of imperfections in the radio environment map (REM) information on the performance of cognitive radio (CR) systems. Via simulations we explore the relationship between the required precision of the REM and various channel/system properties. For example, the degree of spatial correla...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,722
2212.01757	Languages You Know Influence Those You Learn: Impact of Language Characteristics on Multi-Lingual Text-to-Text Transfer	Multi-lingual language models (LM), such as mBERT, XLM-R, mT5, mBART, have been remarkably successful in enabling natural language tasks in low-resource languages through cross-lingual transfer from high-resource ones. In this work, we try to better understand how such models, specifically mT5, transfer any linguisti...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	334,561
1811.00183	Designing an Effective Metric Learning Pipeline for Speaker Diarization	State-of-the-art speaker diarization systems utilize knowledge from external data, in the form of a pre-trained distance metric, to effectively determine relative speaker identities to unseen data. However, much of recent focus has been on choosing the appropriate feature extractor, ranging from pre-trained $i-$vectors...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,024
2103.03938	Causal Analysis of Agent Behavior for AI Safety	As machine learning systems become more powerful they also become increasingly unpredictable and opaque. Yet, finding human-understandable explanations of how they work is essential for their safe deployment. This technical report illustrates a methodology for investigating the causal mechanisms that drive the behaviou...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	223,462
q-bio/0411030	Statistical Mechanics Characterization of Neuronal Mosaics	The spatial distribution of neuronal cells is an important requirement for achieving proper neuronal function in several parts of the nervous system of most animals. For instance, specific distribution of photoreceptors and related neuronal cells, particularly the ganglion cells, in mammal's retina is required in order...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	540,844
2404.05365	NLP Progress in Indigenous Latin American Languages	The paper focuses on the marginalization of indigenous language communities in the face of rapid technological advancements. We highlight the cultural richness of these languages and the risk they face of being overlooked in the realm of Natural Language Processing (NLP). We aim to bridge the gap between these communit...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	445,061
1801.10287	An Incremental Off-policy Search in a Model-free Markov Decision Process Using a Single Sample Path	In this paper, we consider a modified version of the control problem in a model free Markov decision process (MDP) setting with large state and action spaces. The control problem most commonly addressed in the contemporary literature is to find an optimal policy which maximizes the value function, i.e., the long run di...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	89,257
2410.01649	shapiq: Shapley Interactions for Machine Learning	Originally rooted in game theory, the Shapley Value (SV) has recently become an important tool in machine learning research. Perhaps most notably, it is used for feature attribution and data valuation in explainable artificial intelligence. Shapley Interactions (SIs) naturally extend the SV and address its limitations ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	493,869
2112.00065	Boosting EfficientNets Ensemble Performance via Pseudo-Labels and Synthetic Images by pix2pixHD for Infection and Ischaemia Classification in Diabetic Foot Ulcers	Diabetic foot ulcers are a common manifestation of lesions on the diabetic foot, a syndrome acquired as a long-term complication of diabetes mellitus. Accompanying neuropathy and vascular damage promote acquisition of pressure injuries and tissue death due to ischaemia. Affected areas are prone to infections, hindering...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	269,024
1910.04456	Breathing deformation model -- application to multi-resolution abdominal MRI	Dynamic MRI is a technique of acquiring a series of images continuously to follow the physiological changes over time. However, such fast imaging results in low resolution images. In this work, abdominal deformation model computed from dynamic low resolution images have been applied to high resolution image, acquired p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	148,773
1307.0846	Semi-supervised Ranking Pursuit	We propose a novel sparse preference learning/ranking algorithm. Our algorithm approximates the true utility function by a weighted sum of basis functions using the squared loss on pairs of data points, and is a generalization of the kernel matching pursuit method. It can operate both in a supervised and a semi-supervi...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	25,583
1907.06571	Adversarial Video Generation on Complex Datasets	Generative models of natural images have progressed towards high fidelity samples by the strong leveraging of scale. We attempt to carry this success to the field of video modeling by showing that large Generative Adversarial Networks trained on the complex Kinetics-600 dataset are able to produce video samples of subs...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	138,655
2407.18038	TiCoSS: Tightening the Coupling between Semantic Segmentation and Stereo Matching within A Joint Learning Framework	Semantic segmentation and stereo matching, respectively analogous to the ventral and dorsal streams in our human brain, are two key components of autonomous driving perception systems. Addressing these two tasks with separate networks is no longer the mainstream direction in developing computer vision algorithms, parti...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	476,220
2409.14198	A Sinkhorn Regularized Adversarial Network for Image Guided DEM Super-resolution using Frequency Selective Hybrid Graph Transformer	Digital Elevation Model (DEM) is an essential aspect in the remote sensing (RS) domain to analyze various applications related to surface elevations. Here, we address the generation of high-resolution (HR) DEMs using HR multi-spectral (MX) satellite imagery as a guide by introducing a novel hybrid transformer model con...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	490,369
2209.11225	Quantum theory in finite dimension cannot explain every general process with finite memory	Arguably, the largest class of stochastic processes generated by means of a finite memory consists of those that are sequences of observations produced by sequential measurements in a suitable generalized probabilistic theory (GPT). These are constructed from a finite-dimensional memory evolving under a set of possible...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	319,117
2111.08600	Towards Real-Time Monocular Depth Estimation for Robotics: A Survey	As an essential component for many autonomous driving and robotic activities such as ego-motion estimation, obstacle avoidance and scene understanding, monocular depth estimation (MDE) has attracted great attention from the computer vision and robotics communities. Over the past decades, a large number of methods have ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	266,754
2204.07205	Expanding the Reach of Research Computing: A Landscape Study	Research-computing continues to play an ever increasing role in academia. Access to computing resources, however, varies greatly between institutions. Sustaining the growing need for computing skills and access to advanced cyberinfrastructure requires that computing resources be available to students at all levels of s...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	291,605
2212.04120	Denoising Self-attentive Sequential Recommendation	Transformer-based sequential recommenders are very powerful for capturing both short-term and long-term sequential item dependencies. This is mainly attributed to their unique self-attention networks to exploit pairwise item-item interactions within the sequence. However, real-world item sequences are often noisy, whic...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	335,335
1604.08418	Stable Throughput Region of the Two-User Broadcast Channel	In this paper we consider the two-user broadcast channel and we characterize its stable throughout region. We start the analysis by providing the stability region for the general case without any specific considerations on transmission and reception mechanisms. We also provide conditions for the stable throughput regio...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	55,210
2406.08952	Self-orthogonal flags of codes and translation of flags of algebraic geometry codes	A flag $C_0 \subsetneq C_1 \cdots \subsetneq C_s \subsetneq {\mathbb F}_q^n $ of linear codes is said to be self-orthogonal if the duals of the codes in the flag satisfy $C_{i}^\perp=C_{s-i}$, and it is said to satisfy the isometry-dual property with respect to an isometry vector ${\bf x}$ if $C_i^\perp={\bf x} C_{s-i}...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	463,703
2207.02152	UniCR: Universally Approximated Certified Robustness via Randomized Smoothing	We study certified robustness of machine learning classifiers against adversarial perturbations. In particular, we propose the first universally approximated certified robustness (UniCR) framework, which can approximate the robustness certification of any input on any classifier against any $\ell_p$ perturbations with ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	306,417
2412.16876	MAGIC++: Efficient and Resilient Modality-Agnostic Semantic Segmentation via Hierarchical Modality Selection	In this paper, we address the challenging modality-agnostic semantic segmentation (MaSS), aiming at centering the value of every modality at every feature granularity. Training with all available visual modalities and effectively fusing an arbitrary combination of them is essential for robust multi-modal fusion in sema...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	519,725
2002.00251	Multi-Modal Music Information Retrieval: Augmenting Audio-Analysis with Visual Computing for Improved Music Video Analysis	This thesis combines audio-analysis with computer vision to approach Music Information Retrieval (MIR) tasks from a multi-modal perspective. This thesis focuses on the information provided by the visual layer of music videos and how it can be harnessed to augment and improve tasks of the MIR research domain. The main h...	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false	false	false	true	162,304
2306.08433	"Definition Modeling: To model definitions." Generating Definitions With Little to No Semantics	Definition Modeling, the task of generating definitions, was first proposed as a means to evaluate the semantic quality of word embeddings-a coherent lexical semantic representations of a word in context should contain all the information necessary to generate its definition. The relative novelty of this task entails t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	373,413
2312.03612	Physical Symbolic Optimization	We present a framework for constraining the automatic sequential generation of equations to obey the rules of dimensional analysis by construction. Combining this approach with reinforcement learning, we built $\Phi$-SO, a Physical Symbolic Optimization method for recovering analytical functions from physical data leve...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	413,326
2301.04050	Design, Modeling and Control of a Quadruped Robot SPIDAR: Spherically Vectorable and Distributed Rotors Assisted Air-Ground Amphibious Quadruped Robot	Multimodal locomotion capability is an emerging topic in robotics field, and various novel mobile robots have been developed to enable the maneuvering in both terrestrial and aerial domains. Among these hybrid robots, several state-of-the-art bipedal \robots enable the complex walking motion which is interlaced with fl...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	339,962
2309.00189	Data-Driven Safety Filter: An Input-Output Perspective	Implementation of learning-based control remains challenging due to the absence of safety guarantees. Safe control methods have turned to model-based safety filters to address these challenges, but this is paradoxical when the ultimate goal is a model-free, data-driven control solution. Addressing the core question of ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	389,225
1804.01882	Hyperbolic Entailment Cones for Learning Hierarchical Embeddings	Learning graph representations via low-dimensional embeddings that preserve relevant network properties is an important class of problems in machine learning. We here present a novel method to embed directed acyclic graphs. Following prior work, we first advocate for using hyperbolic spaces which provably model tree-li...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	94,303
2306.09132	Enlarged Large Margin Loss for Imbalanced Classification	We propose a novel loss function for imbalanced classification. LDAM loss, which minimizes a margin-based generalization bound, is widely utilized for class-imbalanced image classification. Although, by using LDAM loss, it is possible to obtain large margins for the minority classes and small margins for the majority c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	373,691
2409.00057	First Single-Carrier Transmission at Net Data Rates of 1.6 Tb/s over 9075 km and 2.4 Tb/s over 1210 km Using 300 GBd Dual-Polarization Signals and Probabilistic Constellation Shaping	We report long-haul transmissions of single-carrier 300 GBd dual-polarization signals with optical arbitrary waveform generation and measurement. We demonstrate net 1.6 Tb/s over 9075 km with PCS-16QAM and 2.4 Tb/s over 1210 km with PCS-36QAM.	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	484,746
2404.16411	Label-Free Topic-Focused Summarization Using Query Augmentation	In today's data and information-rich world, summarization techniques are essential in harnessing vast text to extract key information and enhance decision-making and efficiency. In particular, topic-focused summarization is important due to its ability to tailor content to specific aspects of an extended text. However,...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	449,484
1408.6959	Heterogeneous Recovery Rates against SIS Epidemics in Directed Networks	The nodes in communication networks are possibly and most likely equipped with different recovery resources, which allow them to recover from a virus with different rates. In this paper, we aim to understand know how to allocate the limited recovery resources to efficiently prevent the spreading of epidemics. We study ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	35,682
2308.01677	Efficiency of First-Order Methods for Low-Rank Tensor Recovery with the Tensor Nuclear Norm Under Strict Complementarity	We consider convex relaxations for recovering low-rank tensors based on constrained minimization over a ball induced by the tensor nuclear norm, recently introduced in \cite{tensor_tSVD}. We build on a recent line of results that considered convex relaxations for the recovery of low-rank matrices and established that u...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	383,329
1208.2787	Analysis and Construction of Functional Regenerating Codes with Uncoded Repair for Distributed Storage Systems	Modern distributed storage systems apply redundancy coding techniques to stored data. One form of redundancy is based on regenerating codes, which can minimize the repair bandwidth, i.e., the amount of data transferred when repairing a failed storage node. Existing regenerating codes mainly require surviving storage no...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	18,069
2401.09804	Clickbait vs. Quality: How Engagement-Based Optimization Shapes the Content Landscape in Online Platforms	Online content platforms commonly use engagement-based optimization when making recommendations. This encourages content creators to invest in quality, but also rewards gaming tricks such as clickbait. To understand the total impact on the content landscape, we study a game between content creators competing on the bas...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	422,395
1910.13088	Estimating the Density of States of Boolean Satisfiability Problems on Classical and Quantum Computing Platforms	Given a Boolean formula $\phi(x)$ in conjunctive normal form (CNF), the density of states counts the number of variable assignments that violate exactly $e$ clauses, for all values of $e$. Thus, the density of states is a histogram of the number of unsatisfied clauses over all possible assignments. This computation gen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	151,293
2408.10287	Recognizing Beam Profiles from Silicon Photonics Gratings using Transformer Model	Over the past decade, there has been extensive work in developing integrated silicon photonics (SiPh) gratings for the optical addressing of trapped ion qubits in the ion trap quantum computing community. However, when viewing beam profiles from infrared (IR) cameras, it is often difficult to determine the correspondin...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	481,802
2111.05955	Keys to Accurate Feature Extraction Using Residual Spiking Neural Networks	Spiking neural networks (SNNs) have become an interesting alternative to conventional artificial neural networks (ANN) thanks to their temporal processing capabilities and energy efficient implementations in neuromorphic hardware. However the challenges involved in training SNNs have limited their performance in terms ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	265,928
2112.12911	Cluster-guided Image Synthesis with Unconditional Models	Generative Adversarial Networks (GANs) are the driving force behind the state-of-the-art in image generation. Despite their ability to synthesize high-resolution photo-realistic images, generating content with on-demand conditioning of different granularity remains a challenge. This challenge is usually tackled by anno...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	273,079
2402.02082	GliDe with a CaPE: A Low-Hassle Method to Accelerate Speculative Decoding	Speculative decoding is a relatively new decoding framework that leverages small and efficient draft models to reduce the latency of LLMs. In this study, we introduce GliDe and CaPE, two low-hassle modifications to vanilla speculative decoding to further improve the decoding speed of a frozen LLM. Specifically, GliDe i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	426,375
2502.03038	The Cake that is Intelligence and Who Gets to Bake it: An AI Analogy and its Implications for Participation	In a widely popular analogy by Turing Award Laureate Yann LeCun, machine intelligence has been compared to cake - where unsupervised learning forms the base, supervised learning adds the icing, and reinforcement learning is the cherry on top. We expand this 'cake that is intelligence' analogy from a simple structural m...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	530,573
2101.04224	Challenges and approaches to time-series forecasting in data center telemetry: A Survey	Time-series forecasting has been an important research domain for so many years. Its applications include ECG predictions, sales forecasting, weather conditions, even COVID-19 spread predictions. These applications have motivated many researchers to figure out an optimal forecasting approach, but the modeling approach ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	215,090
2310.00436	Enhancing Representation Generalization in Authorship Identification	Authorship identification ascertains the authorship of texts whose origins remain undisclosed. That authorship identification techniques work as reliably as they do has been attributed to the fact that authorial style is properly captured and represented. Although modern authorship identification methods have evolved s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	395,982
1603.05614	Streaming Algorithms for News and Scientific Literature Recommendation: Submodular Maximization with a d-Knapsack Constraint	Submodular maximization problems belong to the family of combinatorial optimization problems and enjoy wide applications. In this paper, we focus on the problem of maximizing a monotone submodular function subject to a $d$-knapsack constraint, for which we propose a streaming algorithm that achieves a $\left(\frac{1}{1...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	53,380
2403.12422	Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization	Pretraining transformers are generally time-consuming. Fully quantized training (FQT) is a promising approach to speed up pretraining. However, most FQT methods adopt a quantize-compute-dequantize procedure, which often leads to suboptimal speedup and significant performance degradation when used in transformers due to...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	439,174
2201.05337	A Survey of Controllable Text Generation using Transformer-based Pre-trained Language Models	Controllable Text Generation (CTG) is emerging area in the field of natural language generation (NLG). It is regarded as crucial for the development of advanced text generation technologies that better meet the specific constraints in practical applications. In recent years, methods using large-scale pre-trained langua...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	275,364
1701.08946	Variable selection for clustering with Gaussian mixture models: state of the art	The mixture models have become widely used in clustering, given its probabilistic framework in which its based, however, for modern databases that are characterized by their large size, these models behave disappointingly in setting out the model, making essential the selection of relevant variables for this type of cl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	67,561
1805.01702	Beyond the Click-Through Rate: Web Link Selection with Multi-level Feedback	The web link selection problem is to select a small subset of web links from a large web link pool, and to place the selected links on a web page that can only accommodate a limited number of links, e.g., advertisements, recommendations, or news feeds. Despite the long concerned click-through rate which reflects the at...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	96,696
1101.4999	List decoding of a class of affine variety codes	Consider a polynomial $F$ in $m$ variables and a finite point ensemble $S=S_1 \times ... \times S_m$. When given the leading monomial of $F$ with respect to a lexicographic ordering we derive improved information on the possible number of zeros of $F$ of multiplicity at least $r$ from $S$. We then use this information ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,922
2404.07200	Toward a Better Understanding of Fourier Neural Operators from a Spectral Perspective	In solving partial differential equations (PDEs), Fourier Neural Operators (FNOs) have exhibited notable effectiveness. However, FNO is observed to be ineffective with large Fourier kernels that parameterize more frequencies. Current solutions rely on setting small kernels, restricting FNO's ability to capture complex ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	445,752
2208.04028	Deep Computational Model for the Inference of Ventricular Activation Properties	Patient-specific cardiac computational models are essential for the efficient realization of precision medicine and in-silico clinical trials using digital twins. Cardiac digital twins can provide non-invasive characterizations of cardiac functions for individual patients, and therefore are promising for the patient-sp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	311,974
2411.01432	Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning	Meta-learning offers a promising avenue for few-shot learning (FSL), enabling models to glean a generalizable feature embedding through episodic training on synthetic FSL tasks in a source domain. Yet, in practical scenarios where the target task diverges from that in the source domain, meta-learning based method is su...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	505,071
2205.10692	All You Need Is Logs: Improving Code Completion by Learning from Anonymous IDE Usage Logs	In this work, we propose an approach for collecting completion usage logs from the users in an IDE and using them to train a machine learning based model for ranking completion candidates. We developed a set of features that describe completion candidates and their context, and deployed their anonymized collection in t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	297,821
2406.08847	Roping in Uncertainty: Robustness and Regularization in Markov Games	We study robust Markov games (RMG) with $s$-rectangular uncertainty. We show a general equivalence between computing a robust Nash equilibrium (RNE) of a $s$-rectangular RMG and computing a Nash equilibrium (NE) of an appropriately constructed regularized MG. The equivalence result yields a planning algorithm for solvi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	463,656
2408.14698	Smart Multi-Modal Search: Contextual Sparse and Dense Embedding Integration in Adobe Express	As user content and queries become increasingly multi-modal, the need for effective multi-modal search systems has grown. Traditional search systems often rely on textual and metadata annotations for indexed images, while multi-modal embeddings like CLIP enable direct search using text and image embeddings. However, em...	false	false	false	false	true	true	false	false	true	false	false	true	false	false	false	false	false	false	483,633
2212.03411	A Flexible Nadaraya-Watson Head Can Offer Explainable and Calibrated Classification	In this paper, we empirically analyze a simple, non-learnable, and nonparametric Nadaraya-Watson (NW) prediction head that can be used with any neural network architecture. In the NW head, the prediction is a weighted average of labels from a support set. The weights are computed from distances between the query featur...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	335,108
2304.14630	Let the Chart Spark: Embedding Semantic Context into Chart with Text-to-Image Generative Model	Pictorial visualization seamlessly integrates data and semantic context into visual representation, conveying complex information in a manner that is both engaging and informative. Extensive studies have been devoted to developing authoring tools to simplify the creation of pictorial visualizations. However, mainstream...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	361,046
2106.07582	Non Gaussian Denoising Diffusion Models	Generative diffusion processes are an emerging and effective tool for image and speech generation. In the existing methods, the underline noise distribution of the diffusion process is Gaussian noise. However, fitting distributions with more degrees of freedom, could help the performance of such generative models. In t...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	240,984
1901.05623	Double variational principle for mean dimension	We develop a variational principle between mean dimension theory and rate distortion theory. We consider a minimax problem about the rate distortion dimension with respect to two variables (metrics and measures). We prove that the minimax value is equal to the mean dimension for a dynamical system with the marker prope...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	118,825
2104.02478	Topological Regularization for Graph Neural Networks Augmentation	The complexity and non-Euclidean structure of graph data hinder the development of data augmentation methods similar to those in computer vision. In this paper, we propose a feature augmentation method for graph nodes based on topological regularization, in which topological structure information is introduced into end...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	228,732
2409.09357	Joint Semantic Knowledge Distillation and Masked Acoustic Modeling for Full-band Speech Restoration with Improved Intelligibility	Speech restoration aims at restoring full-band speech with high quality and intelligibility, considering a diverse set of distortions. MaskSR is a recently proposed generative model for this task. As other models of its kind, MaskSR attains high quality but, as we show, intelligibility can be substantially improved. We...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	488,287
2210.01797	Ten Years after ImageNet: A 360{\deg} Perspective on AI	It is ten years since neural networks made their spectacular comeback. Prompted by this anniversary, we take a holistic perspective on Artificial Intelligence (AI). Supervised Learning for cognitive tasks is effectively solved - provided we have enough high-quality labeled data. However, deep neural network models are ...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	321,405
1206.6380	Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring	In this paper we address the following question: Can we approximately sample from a Bayesian posterior distribution if we are only allowed to touch a small mini-batch of data-items for every sample we generate?. An algorithm based on the Langevin equation with stochastic gradients (SGLD) was previously proposed to solv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	16,915
2406.17810	PIC2O-Sim: A Physics-Inspired Causality-Aware Dynamic Convolutional Neural Operator for Ultra-Fast Photonic Device FDTD Simulation	The finite-difference time-domain (FDTD) method, which is important in photonic hardware design flow, is widely adopted to solve time-domain Maxwell equations. However, FDTD is known for its prohibitive runtime cost, taking minutes to hours to simulate a single device. Recently, AI has been applied to realize orders-of...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	467,741
1307.5736	Speaker Independent Continuous Speech to Text Converter for Mobile Application	An efficient speech to text converter for mobile application is presented in this work. The prime motive is to formulate a system which would give optimum performance in terms of complexity, accuracy, delay and memory requirements for mobile environment. The speech to text converter consists of two stages namely front-...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	25,979
1011.0520	Adaptive Algorithms for Coverage Control and Space Partitioning in Mobile Robotic Networks	This paper considers deployment problems where a mobile robotic network must optimize its configuration in a distributed way in order to minimize a steady-state cost function that depends on the spatial distribution of certain probabilistic events of interest. Moreover, it is assumed that the event location distributio...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	8,117
2112.06204	Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant Setup	Training a model to provide natural language explanations (NLEs) for its predictions usually requires the acquisition of task-specific NLEs, which is time- and resource-consuming. A potential solution is the few-shot out-of-domain transfer of NLEs from a parent task with many NLEs to a child task. In this work, we exam...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	271,095
1506.05254	Gradient Estimation Using Stochastic Computation Graphs	In a variety of problems originating in supervised, unsupervised, and reinforcement learning, the loss function is defined by an expectation over a collection of random variables, which might be part of a probabilistic model or the external world. Estimating the gradient of this loss function, using samples, lies at th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	44,280
2410.04147	Can the Variation of Model Weights be used as a Criterion for Self-Paced Multilingual NMT?	Many-to-one neural machine translation systems improve over one-to-one systems when training data is scarce. In this paper, we design and test a novel algorithm for selecting the language of minibatches when training such systems. The algorithm changes the language of the minibatch when the weights of the model do not ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	495,145
2109.07783	Towards Non-Line-of-Sight Photography	Non-line-of-sight (NLOS) imaging is based on capturing the multi-bounce indirect reflections from the hidden objects. Active NLOS imaging systems rely on the capture of the time of flight of light through the scene, and have shown great promise for the accurate and robust reconstruction of hidden scenes without the nee...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	255,654
2212.10937	DCC: A Cascade based Approach to Detect Communities in Social Networks	Community detection in Social Networks is associated with finding and grouping the most similar nodes inherent in the network. These similar nodes are identified by computing tie strength. Stronger ties indicates higher proximity shared by connected node pairs. This work is motivated by Granovetter's argument that sugg...	false	false	false	true	false	true	true	false	false	false	false	true	false	false	false	false	false	false	337,660
2003.13848	Code Prediction by Feeding Trees to Transformers	We advance the state-of-the-art in the accuracy of code prediction (next token prediction) used in autocomplete systems. First, we report that using the recently proposed Transformer architecture even out-of-the-box outperforms previous neural and non-neural systems for code prediction. We then show that by making the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	170,325
2102.07539	Crowdsourcing Parallel Corpus for English-Oromo Neural Machine Translation using Community Engagement Platform	Even though Afaan Oromo is the most widely spoken language in the Cushitic family by more than fifty million people in the Horn and East Africa, it is surprisingly resource-scarce from a technological point of view. The increasing amount of various useful documents written in English language brings to investigate the ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	220,139
1901.03857	Deep-learning-based identification of odontogenic keratocysts in hematoxylin- and eosin-stained jaw cyst specimens	The aim of this study was to develop a digital histopathology system for identifying odontogenic keratocysts in hematoxylin- and eosin-stained tissue specimens of jaw cysts. Approximately 5000 microscopy images with 400$\times$ magnification were obtained from 199 odontogenic keratocysts, 208 dentigerous cysts, and 55 ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	118,502
2005.06313	Stealth Communication with Vanishing Power over Binary Symmetric Channels	A framework for stealth communication with vanishing power (VP) is presented by studying binary symmetric channels. Coding theorems are proved by modifying Gallager's error exponents for VP and by applying resolvability exponents. The analysis unifies and generalizes existing rate bounds for covert and stealth communic...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	176,974
1302.3860	ScalienDB: Designing and Implementing a Distributed Database using Paxos	ScalienDB is a scalable, replicated database built on top of the Paxos algorithm. It was developed from 2010 to 2012, when the startup backing it failed. This paper discusses the design decisions of the distributed database, describes interesting parts of the C++ codebase and enumerates lessons learned putting ScalienD...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	22,098

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