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- short-paperMay 2024
eAIEDF: Extended AI Error Diagnosis Flowchart for Automatically Identifying Misprediction Causes in Production Models
ICSE-Companion '24: Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion ProceedingsApril 2024, Pages 335–336https://doi.org/10.1145/3639478.3643104MLOps, addressing operational issues in machine learning, has gained attention for enhancing the performance of production models. A core challenge is efficiently understanding the causes of mispredictions, as current methods often require labor-...
- research-articleJanuary 2024
Error analysis for face coded modulation system
AbstractThis paper discusses a new mapping scheme known as face coded modulation (FCM) system. In FCM, peak energy symbols are mapped onto an innermost ring according to the eight sockets in the human face, that is, brain, mouth, nostrils, eyes and ...
This paper proposes a new modulation system called Face Coded Modulation that offers flexibility in APSK modulation. It borrows from the 8 nodes found in the human face to map symbols. New PAPR levels and energy efficiency for MQAM are produced. A new ...
- research-articleNovember 2023
Design and Analysis of High Performance Heterogeneous Block-based Approximate Adders
ACM Transactions on Embedded Computing Systems (TECS), Volume 22, Issue 6Article No.: 106, Pages 1–32https://doi.org/10.1145/3625686Approximate computing is an emerging paradigm to improve the power and performance efficiency of error-resilient applications. As adders are one of the key components in almost all processing systems, a significant amount of research has been carried out ...
- short-paperOctober 2023
Quantitative Decomposition of Prediction Errors Revealing Multi-Cause Impacts: An Insightful Framework for MLOps
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge ManagementOctober 2023, Pages 4259–4263https://doi.org/10.1145/3583780.3615238As machine learning applications expand in various industries, MLOps, which enables continuous model operation and improvement, becomes increasingly significant. Identifying causes of prediction errors, such as low model performance or anomalous samples, ...
- research-articleOctober 2023
Contextual Gaps in Machine Learning for Mental Illness Prediction: The Case of Diagnostic Disclosures
Proceedings of the ACM on Human-Computer Interaction (PACMHCI), Volume 7, Issue CSCW2Article No.: 332, Pages 1–27https://doi.org/10.1145/3610181Getting training data for machine learning (ML) prediction of mental illness on social media data is labor intensive. To work around this, ML teams will extrapolate proxy signals, or alternative signs from data to evaluate illness status and create ...
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- research-articleJuly 2023
Temporal Set Inversion for Animated Implicits
ACM Transactions on Graphics (TOG), Volume 42, Issue 4Article No.: 134, Pages 1–18https://doi.org/10.1145/3592448We exploit the temporal coherence of closed-form animated implicit surfaces by locally re-evaluating an octree-like discretization of the implicit field only as and where is necessary to rigorously maintain a global error invariant over time, thereby ...
- research-articleMay 2023
Peak-Load Energy Management by Direct Load Control Contracts
Management Science (MANS), Volume 69, Issue 5May 2023, Pages 2788–2813https://doi.org/10.1287/mnsc.2022.4493We study direct load control contracts that utilities use to curtail customers’ electricity consumption during peak-load periods. These contracts place limits on the number of calls and total number of hours of power reduction per customer per year as ...
- research-articleJanuary 2023
Numerical simulation and convergence analysis for Riemann-Liouville fractional initial value problem involving weak singularity
International Journal of Computing Science and Mathematics (IJCSM), Volume 18, Issue 42023, Pages 340–349https://doi.org/10.1504/ijcsm.2023.135045The present work considers a Riemann-Liouville fractional initial value problem (IVP) associated with homogeneous initial condition involving a weak singularity near the origin. Due to presence of initial singularity, an initial layer occurs at t = 0. The ...
- research-articleDecember 2022
Error Analysis of Surrogate Models Constructed Through Operations on Submodels
Mathematics of Operations Research (MOOR), Volume 49, Issue 1February 2024, Pages 1–18https://doi.org/10.1287/moor.2022.1344Model-based methods are popular in derivative-free optimization (DFO). In most of them, a single model function is built to approximate the objective function. This is generally based on the assumption that the objective function is one black box. However,...
- short-paperJune 2022
A prototype gutenberg-hathitrust sentence-level parallel corpus for OCR error analysis: pilot investigations
JCDL '22: Proceedings of the 22nd ACM/IEEE Joint Conference on Digital LibrariesJune 2022, Article No.: 45, Pages 1–5https://doi.org/10.1145/3529372.3533298This exploratory study proposes a prototype sentence-level parallel corpus to support studying optical character recognition (OCR) quality in curated digitized library collections. Existing data resources, such as ICDAR2019[21] and GT4HistOCR[23], ...
- research-articleJanuary 2022
Hardware implementation of approximate multipliers for signal processing applications
International Journal of Wireless and Mobile Computing (IJWMC), Volume 23, Issue 3-42022, Pages 302–309https://doi.org/10.1504/ijwmc.2022.127595Multiplication is a complex and substantial arithmetic task involved in signal processing applications. The hardware complexity of the multiplier is always high when compared with any other arithmetic operation. Approximate multiplication is a common ...
- research-articleJanuary 2022
A New Lagrange Multiplier Approach for Constructing Structure Preserving Schemes, II. Bound Preserving
SIAM Journal on Numerical Analysis (SINUM), Volume 60, Issue 3Jun 2022, Pages 970–998https://doi.org/10.1137/21M144877XIn the second part of this series, we use the Lagrange multiplier approach proposed in the first part [Comput. Methods Appl. Mech. Engr., 391 (2022), 114585] to construct efficient and accurate bound and/or mass preserving schemes for a class of ...
- research-articleJanuary 2022
Fast Deterministic Approximation of Symmetric Indefinite Kernel Matrices with High Dimensional Datasets
SIAM Journal on Matrix Analysis and Applications (SIMAX), Volume 43, Issue 2Jun 2022, Pages 1003–1028https://doi.org/10.1137/21M1424627Kernel methods are used frequently in various applications of machine learning. For large-scale high dimensional applications, the success of kernel methods hinges on the ability to operate certain large dense kernel matrix $K$. An enormous amount of ...
- research-articleJanuary 2022
Randomized Quaternion Singular Value Decomposition for Low-Rank Matrix Approximation
SIAM Journal on Scientific Computing (SISC), Volume 44, Issue 2Apr 2022, Pages A870–A900https://doi.org/10.1137/21M1418319This paper presents a randomized quaternion singular value decomposition (QSVD) algorithm for low-rank matrix approximation problems, which are widely used in color face recognition, video compression, and signal processing problems. With quaternion ...
- research-articleJanuary 2022
Sharper Error Estimates for Virtual Elements and a Bubble-Enriched Version
SIAM Journal on Numerical Analysis (SINUM), Volume 60, Issue 4Aug 2022, Pages 1853–1878https://doi.org/10.1137/21M1411275In the present contribution we develop a sharper error analysis for the Virtual Element Method, applied to a model elliptic problem, that separates the element boundary and element interior contributions to the error. As a consequence we are able to ...
- research-articleJanuary 2022
Exponential Integrators for Quasilinear Wave-Type Equations
SIAM Journal on Numerical Analysis (SINUM), Volume 60, Issue 3Jun 2022, Pages 1472–1493https://doi.org/10.1137/21M1410579In this paper we propose two exponential integrators of first and second order applied to a class of quasilinear wave-type equations. The analytical framework is an extension of the classical Kato framework and covers quasilinear Maxwell's equations in ...
- research-articleJanuary 2022
Hybrid High-Order and Weak Galerkin Methods for the Biharmonic Problem
SIAM Journal on Numerical Analysis (SINUM), Volume 60, Issue 5Oct 2022, Pages 2626–2656https://doi.org/10.1137/21M1408555We devise and analyze two hybrid high-order (HHO) methods for the numerical approximation of the biharmonic problem. The methods support polyhedral meshes, rely on the primal formulation of the problem, and deliver $O(h^{k+1})$ $H^2$-error estimates when ...
- research-articleJanuary 2022
Strong Convergence Order for the Scheme of Fractional Diffusion Equation Driven by Fractional Gaussian Noise
SIAM Journal on Numerical Analysis (SINUM), Volume 60, Issue 4Aug 2022, Pages 1879–1904https://doi.org/10.1137/20M1356270Fractional Gaussian noise models the time series with long-range dependence; when the Hurst index $H\in(1/2,1)$, it has positive correlation reflecting a persistent autocorrelation structure. This paper studies the numerical method for solving the ...
- research-articleNovember 2021
Error Refactor loss based on error analysis in image classification
IET Computer Vision (CVI2), Volume 16, Issue 2March 2022, Pages 192–203https://doi.org/10.1049/cvi2.12079AbstractThe loss function is a criterion to evaluate the learning quality of a deep convolutional neural network, which represents the gap between prediction and ground truth. However, as the most commonly used loss function in image classification tasks, ...
- research-articleJuly 2021
Improving Power of DSP and CNN Hardware Accelerators Using Approximate Floating-point Multipliers
ACM Transactions on Embedded Computing Systems (TECS), Volume 20, Issue 5Article No.: 39, Pages 1–21https://doi.org/10.1145/3448980Approximate computing has emerged as a promising design alternative for delivering power-efficient systems and circuits by exploiting the inherent error resiliency of numerous applications. The current article aims to tackle the increased hardware cost ...