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View article: Cross-Process Defect Attribution using Potential Loss Analysis
Cross-Process Defect Attribution using Potential Loss Analysis Open
Cross-process root-cause analysis of wafer defects is among the most critical yet challenging tasks in semiconductor manufacturing due to the heterogeneity and combinatorial nature of processes along the processing route. This paper presen…
View article: Wafer Defect Root Cause Analysis with Partial Trajectory Regression DM: Big Data Management and Machine Learning
Wafer Defect Root Cause Analysis with Partial Trajectory Regression DM: Big Data Management and Machine Learning Open
Identifying upstream processes responsible for wafer defects is challenging due to the combinatorial nature of process flows and the inherent variability in processing routes, which arises from factors such as rework operations and random …
View article: Sequence-Aware Inline Measurement Attribution for Good-Bad Wafer Diagnosis : DM: Big Data Management and Machine Learning
Sequence-Aware Inline Measurement Attribution for Good-Bad Wafer Diagnosis : DM: Big Data Management and Machine Learning Open
How can we identify problematic upstream processes when a certain type of wafer defect starts appearing at a quality checkpoint? Given the complexity of modern semiconductor manufacturing, which involves thousands of process steps, cross-p…
View article: Improving Transformers using Faithful Positional Encoding
Improving Transformers using Faithful Positional Encoding Open
We propose a new positional encoding method for a neural network architecture called the Transformer. Unlike the standard sinusoidal positional encoding, our approach is based on solid mathematical grounds and has a guarantee of not losing…
View article: Decentralized Collaborative Learning Framework with External Privacy Leakage Analysis
Decentralized Collaborative Learning Framework with External Privacy Leakage Analysis Open
This paper presents two methodological advancements in decentralized multi-task learning under privacy constraints, aiming to pave the way for future developments in next-generation Blockchain platforms. First, we expand the existing frame…
View article: A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible food
A resource-constrained stochastic scheduling algorithm for homeless street outreach and gleaning edible food Open
We developed a common algorithmic solution addressing the problem of resource-constrained outreach encountered by social change organizations with different missions and operations: Breaking Ground -- an organization that helps individuals…
View article: Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes Open
We address the problem of learning Granger causality from asynchronous, interdependent, multi-type event sequences. In particular, we are interested in discovering instance-level causal structures in an unsupervised manner. Instance-level …
View article: Identifying primary aldosteronism patients who require adrenal venous sampling: a multi-center study
Identifying primary aldosteronism patients who require adrenal venous sampling: a multi-center study Open
View article: Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution
Generative Perturbation Analysis for Probabilistic Black-Box Anomaly Attribution Open
We address the task of probabilistic anomaly attribution in the black-box regression setting, where the goal is to compute the probability distribution of the attribution score of each input variable, given an observed anomaly. The trainin…
View article: Black-Box Anomaly Attribution
Black-Box Anomaly Attribution Open
When the prediction of a black-box machine learning model deviates from the true observation, what can be said about the reason behind that deviation? This is a fundamental and ubiquitous question that the end user in a business or industr…
View article: Diagnostic spatio-temporal transformer with faithful encoding
Diagnostic spatio-temporal transformer with faithful encoding Open
View article: Advances in Knowledge Discovery and Data Mining
Advances in Knowledge Discovery and Data Mining Open
View article: Cardinality-Regularized Hawkes-Granger Model
Cardinality-Regularized Hawkes-Granger Model Open
We propose a new sparse Granger-causal learning framework for temporal event data. We focus on a specific class of point processes called the Hawkes process. We begin by pointing out that most of the existing sparse causal learning algorit…
View article: Decentralized Collaborative Learning with Probabilistic Data Protection
Decentralized Collaborative Learning with Probabilistic Data Protection Open
We discuss future directions of Blockchain as a collaborative value co-creation platform, in which network participants can gain extra insights that cannot be accessed when disconnected from the others. As such, we propose a decentralized …
View article: Targeted Advertising on Social Networks Using Online Variational Tensor Regression
Targeted Advertising on Social Networks Using Online Variational Tensor Regression Open
This paper is concerned with online targeted advertising on social networks. The main technical task we address is to estimate the activation probability for user pairs, which quantifies the influence one user may have on another towards p…
View article: Directed Graph Auto-Encoders
Directed Graph Auto-Encoders Open
We introduce a new class of auto-encoders for directed graphs, motivated by a direct extension of the Weisfeiler-Leman algorithm to pairs of node labels. The proposed model learns pairs of interpretable latent representations for the nodes…
View article: Directed Graph Auto-Encoders
Directed Graph Auto-Encoders Open
We introduce a new class of auto-encoders for directed graphs, motivated by a direct extension of the Weisfeiler-Leman algorithm to pairs of node labels. The proposed model learns pairs of interpretable latent representations for the nodes…
View article: Decentralized Collaborative Learning with Probabilistic Data Protection
Decentralized Collaborative Learning with Probabilistic Data Protection Open
We discuss future directions of Blockchain as a collaborative value co-creation platform, in which network participants can gain extra insights that cannot be accessed when disconnected from the others. As such, we propose a decentralized …
View article: Anomaly Attribution with Likelihood Compensation
Anomaly Attribution with Likelihood Compensation Open
This paper addresses the task of explaining anomalous predictions of a black-box regression model. When using a black-box model, such as one to predict building energy consumption from many sensor measurements, we often have a situation wh…
View article: Efficient Protocol for Collaborative Dictionary Learning in Decentralized Networks
Efficient Protocol for Collaborative Dictionary Learning in Decentralized Networks Open
This paper is concerned with the task of collaborative density estimation in the distributed multi-task setting. Major application scenarios include collaborative anomaly detection among distributed industrial assets owned by different com…
View article: Tensorial Change Analysis Using Probabilistic Tensor Regression
Tensorial Change Analysis Using Probabilistic Tensor Regression Open
This paper proposes a new method for change detection and analysis using tensor regression. Change detection in our setting is to detect changes in the relationship between the input tensor and the output scalar while change analysis is to…
View article: <i>ℓ</i><sub>0</sub>-Regularized Sparsity for Probabilistic Mixture Models
<i>ℓ</i><sub>0</sub>-Regularized Sparsity for Probabilistic Mixture Models Open
This paper revisits a classical task of learning probabilistic mixture models. Our major goal is to sparsely learn the mixture weights to automatically determine the right number of clusters. The key idea is to use a novel Bernoulli prior …
View article: Predicting Nocturnal Hypoglycemia from Continuous Glucose Monitoring Data with Extended Prediction Horizon.
Predicting Nocturnal Hypoglycemia from Continuous Glucose Monitoring Data with Extended Prediction Horizon. Open
Nocturnal hypoglycemia is a serious complication of insulin-treated diabetes, which commonly goes undetected. Continuous glucose monitoring (CGM) devices have enabled prediction of impending nocturnal hypoglycemia, however, prior efforts h…
View article: Panasonic VIERA Powered by Firefox OS
Panasonic VIERA Powered by Firefox OS Open