Igor: Crash Deduplication Through Root-Cause Clustering

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The Gm/ID approach has proven to be an efficient technique for the design of low-power analog circuits. Until now it was mostly demonstrated on older CMOS technology nodes. In this paper we will show that the Gm/ID methodology still holds for advanced tech ...

We conducted a comparative user study of the Infinadeck [1] omnidirectional treadmill native control algorithm alongside an approach based on a state observer control scheme combining a kinematic model with error dynamics that allows users to change their ...

Sexual harassment is prevalent at all levels of higher education and research and in all disciplines, which means that engineering education is no exception. Following the #MeToo movement, students have started to report cases of abuses publicly in our ins ...

The acquisition of survey responses is a crucial component in conducting research aimed at comprehending public opinion. However, survey data collection can be arduous, time-consuming, and expensive, with no assurance of an adequate response rate. In this ...

This paper defines a Maximum Likelihood Estimator (MLE) for the admittance matrix estimation of distribution grids, utilising voltage magnitude and power measurements collected only from common, unsychronised measuring devices (Smart Meters). First, we pre ...

Previous works on age of information and erasure channels have dealt with specific models and computed the average age or average peak age for certain settings. In this paper, given a source that produces a letter every T-s seconds and an erasure channel t ...

Soft Magnetic Composites (SMCs) have huge application potential in electrical devices. With the development of additive manufacturing (AM), the properties of SMCs can be boosted. It is therefore required an optimization algorithm to design SMCs considering ...

In this paper, we study the compression of a target two-layer neural network with N nodes into a compressed network with M < N nodes. More precisely, we consider the setting in which the weights of the target network are i.i.d. sub-Gaussian, and we minimiz ...

As the usage of FPGAs spreads, engineers will inevitably employ them in ways unforeseen-or unwanted-by their manufacturers. Xilinx's toolchains offer multiple points for customizing the FPGA compilation flow, but all flows must end with Vivado as it is the ...

Transaction processing is a central part of most database applications. While serializability remains the gold standard for desirable transactional semantics, many database systems offer improved transaction throughput at the expense of introducing potenti ...

Kinetic models of metabolism relate metabolic fluxes, metabolite concentrations and enzyme levels through mechanistic relations, rendering them essential for understanding, predicting and optimizing the behaviour of living organisms. However, due to the la ...

In this work, we present a simple biometric indexing scheme which is binning and retrieving cancelable deep face templates based on frequent binary patterns. The simplicity of the proposed approach makes it applicable to unprotected as well as protected, i ...

Non-Rigid Structure-from-Motion (NRSfM) reconstructs a deformable 3D object from keypoint correspondences established between monocular 2D images. Current NRSfM methods lack statistical robustness, which is the ability to cope with correspondence errors. T ...

A major obstacle to achieving global convergence in distributed and federated learning is the misalignment of gradients across clients, or mini-batches due to heterogeneity and stochasticity of the distributed data. In this work, we show that data heteroge ...

We describe the first gradient methods on Riemannian manifolds to achieve accelerated rates in the non-convex case. Under Lipschitz assumptions on the Riemannian gradient and Hessian of the cost function, these methods find approximate first-order critical ...

To shrink the environmental footprint of housing, reducing dwellings' size is key. There is agreement among scholars on the measures that should be taken to achieve this goal, however their effectiveness and effects have not been sufficiently investigated. ...

State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density. While effective, these data-driven approaches rely on large amount of data annotation to achieve good performance, which stops these models from ...

There are increasing interests in document layout representation learning and understanding. Transformer, with its great power, has become the mainstream model architecture and achieved promising results in this area. As elements in a document layout consi ...

In real-time optimization, the solution quality depends on the model ability to predict the plant KarushKuhn-Tucker (KKT) conditions. In the case of non-parametric plant-model mismatch, one can add input-affine modifiers to the model cost and constraints a ...

This paper investigates the effect of combination policies on the performance of adaptive social learning in non-stationary environments. By analyzing the relation between the error probability and the underlying graph topology, we prove that in the slow a ...

Igor: Crash Deduplication Through Root-Cause Clustering

Chattez avec Graph Search

Design of Low-power Analog Circuits in Advanced Technology Nodes using the Gm/ID Approach

User study of omnidirectional treadmill control algorithms in VR

Supporting Well-Being: A Digital Intervention Model for Disclosing Sexual Harassment in Higher Education

Predicting Survey Response with Quotation-based Modeling: A Case Study on Favorability towards the United States

Maximum likelihood estimation of distribution grid topology and parameters from Smart Meter data

Optima Age Over Erasure Channels

Topology Optimization of Soft Magnetic Composites with Integer Programming

Sharp asymptotics on the compression of two-layer neural networks

Bitfiltrator: A general approach for reverse-engineering Xilinx bitstream formats

Robustness Against Read Committed: A Free Transactional Lunch

Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks

Indexing Protected Deep Face Templates by Frequent Binary Patterns

Robust Isometric Non-Rigid Structure-From-Motion

Implicit Gradient Alignment in Distributed and Federated Learning

An Accelerated First-Order Method for Non-convex Optimization on Manifolds

Shrinking Housing's Size: Using Agent-Based Modelling to Explore Measures for a Reduction of Floor Area Per Capita

Leveraging Self-Supervision for Cross-Domain Crowd Counting

Exploring Heterogeneous Feature Representation for Document Layout Understanding

On improving the efficiency of modifier adaptation via directional information

Optimal Combination Policies For Adaptive Social Learning