Computing with Reads and Writes in the Absence of Step Contention

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In this work, we tackle the task of estimating the 6D pose of an object from point cloud data. While recent learning-based approaches have shown remarkable success on synthetic datasets, we have observed them to fail in the presence of real-world data. We ...

Light and sound waves can move objects through the transfer of linear or angular momentum, which has led to the development of optical and acoustic tweezers, with applications ranging from biomedical engineering to quantum optics. Although impressive manip ...

Enterprises collect data in large volumes and leverage them to drive numerous concurrent decisions and business processes. Their teams deploy multiple applications that often operate concurrently on the same data and infrastructure but have widely differen ...

An electroadhesive gripping system and a method for gripping and manipulating an object are disclosed. The invention provides a novel approach particularly useful to pick fabrics or otherwise flat and flexible objects including a method relying on electroa ...

The study of non-contact manipulation in water, and the ability to robotically control floating objects has gained recent attention due to wide-ranging potential applications, including the analysis of plastic pollution in the oceans and the optimization o ...

Given a hyperelliptic hyperbolic surface S of genus g >= 2, we find bounds on the lengths of homologically independent loops on S. As a consequence, we show that for any lambda is an element of (0, 1) there exists a constant N(lambda) such that every such ...

Multicellular organisms require very well organized and finely balanced cell-cell communication, adhesion and coordination to ensure the organisms homeostasis. These functions rely on specialized receptors placed at the cells membrane whose binding to thei ...

The properties of signal strength and integrated intensity in a scanned imaging system are reviewed. These prop-erties are especially applied to confocal imaging systems, including image scanning microscopy. The integrated intensity, equal to the image of ...

Collaborative learning algorithms, such as distributed SGD (or D-SGD), are prone to faulty machines that may deviate from their prescribed algorithm because of software or hardware bugs, poisoned data or malicious behaviors. While many solutions have been ...

The log law of the wall, joining the inner, near-wall mean velocity profile (MVP) in wall-bounded turbulent flows to the outer region, has been a permanent fixture of turbulence research for over hundred years, but there is still no general agreement on th ...

We introduce the first multitasking vision transformer adapters that learn generalizable task affinities which can be applied to novel tasks and domains. Integrated into an off-the-shelf vision transformer backbone, our adapters can simultaneously solve mu ...

This chapter looks at the intertwined evolution of two different ideas throughout the past century: that of ‘territory’, that has been reshaped and redefined in the field of architecture and urbanism, and that of ‘digital’, that while becoming dominant, ha ...

Visual working memory (VWM) is prone to interference from stored items competing for its limited capacity. Distinctiveness or similarity of the items is acknowledged to affect this competition, such that poor item distinctiveness causes a failure to discri ...

This thesis assesses the surveillance operated on the mobile phone network by governmental actors (intelligence agencies, police, army) and the relationship between monitored spaces and their users. Indeed, some new surveillance devices used by intelligenc ...

When learning from data, leveraging the symmetries of the domain the data lies on is a principled way to combat the curse of dimensionality: it constrains the set of functions to learn from. It is more data efficient than augmentation and gives a generaliz ...

The aim of this paper is to serve as a lightweight introduction to concurrency control for database theorists through a uniform presentation of the work on robustness against Multiversion Read Committed and Snapshot Isolation. ...

This work develops new algorithms with rigorous efficiency guarantees for infinite horizon imitation learning (IL) with linear function approximation without restrictive coherence assumptions. We begin with the minimax formulation of the problem and then o ...

Edge-based and face-based smoothed finite element methods (ES-FEM and FS-FEM, respectively) are modified versions of the finite element method allowing to achieve more accurate results and to reduce sensitivity to mesh distortion, at least for linear eleme ...

Graph sparsification has been studied extensively over the past two decades, culminating in spectral sparsifiers of optimal size (up to constant factors). Spectral hypergraph sparsification is a natural analogue of this problem, for which optimal bounds on ...

Human-robot collaboration requires the contactless estimation of the physical properties of containers manipulated by a person, for example while pouring content in a cup or moving a food box. Acoustic and visual signals can be used to estimate the physica ...

Computing with Reads and Writes in the Absence of Step Contention

Chat with Graph Search

Match Normalization: Learning-Based Point Cloud Registration for 6D Object Pose Estimation in the Real World

Wave-momentum shaping for moving objects in heterogeneous and dynamic media

Oligolithic Cross-task Optimizations across Isolated Workloads

Electroadhesive gripping system and method for gripping an object

Non-contact robotic manipulation of floating objects: exploiting emergent limit cycles

Short homology bases for hyperelliptic hyperbolic surfaces

Combination of dielectrophoretic and hydrodynamic traps for the controlled contact between cells or beads and application to adhesion assays

Signal strength and integrated intensity in confocal and image scanning microscopy

Robust Collaborative Learning with Linear Gradient Overhead

The hunt for the Karman 'constant' revisited

Vision Transformer Adapters for Generalizable Multitask Learning

Between digital and territorial turns: A forking path

Effects of item distinctiveness on the retrieval of objects and object-location bindings from visual working memory

Opacité et transparence dans le design d'un dispositif de surveillance urbain : le cas de l'IMSI catcher

Leveraging topology, geometry, and symmetries for efficient Machine Learning

Concurrency control for database theorists

Proximal Point Imitation Learning

An element-based formulation for ES-FEM and FS-FEM models for implementation in standard solid mechanics finite element codes for 2D and 3D static analysis

Spectral Hypergraph Sparsifiers of Nearly Linear Size

Audio-Visual Object Classification For Human-Robot Collaboration