Results 151 to 160 of about 8,723,820 (234)
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Signal Processing, 2022
Abstract We propose a data denoising method using Extreme Learning Machine (ELM) structure which allows us to use Johnson-Lindenstraus Lemma (JL) for preserving Restricted Isometry Property (RIP) in order to give theoretical guarantees for recovery. Furthermore, we show that the method is equivalent to a robust two-layer ELM that implicitly benefits ...
Ömer Ekmekcioglu +2 more
openaire +4 more sources
Abstract We propose a data denoising method using Extreme Learning Machine (ELM) structure which allows us to use Johnson-Lindenstraus Lemma (JL) for preserving Restricted Isometry Property (RIP) in order to give theoretical guarantees for recovery. Furthermore, we show that the method is equivalent to a robust two-layer ELM that implicitly benefits ...
Ömer Ekmekcioglu +2 more
openaire +4 more sources
2nd International Conference on Dependability of Computer Systems (DepCoS-RELCOMEX '07), 2007
The paper deals with the problem of handling detected faults in computer systems. We present software procedures targeted at fault detection, fault masking and error recovery. They are discussed in the context of standard PC Windows and Linux environments. Various aspects of checkpointing and recovery policies are studied.
A. Lesiak +2 more
openaire +2 more sources
The paper deals with the problem of handling detected faults in computer systems. We present software procedures targeted at fault detection, fault masking and error recovery. They are discussed in the context of standard PC Windows and Linux environments. Various aspects of checkpointing and recovery policies are studied.
A. Lesiak +2 more
openaire +2 more sources
2009 IEEE International Conference on Software Maintenance, 2009
Error recovery in compilers often involves significant amounts of cognitive effort to identify the code and execution points in the compiler that are related to identifying and handling input-program errors. This is because current implementations fail to explicitly identify error-related control dependencies, and to separately characterize the actions
Jeeva Paudel, Christopher Dutchyn
openaire +1 more source
Error recovery in compilers often involves significant amounts of cognitive effort to identify the code and execution points in the compiler that are related to identifying and handling input-program errors. This is because current implementations fail to explicitly identify error-related control dependencies, and to separately characterize the actions
Jeeva Paudel, Christopher Dutchyn
openaire +1 more source
Practical syntactic error recovery
Communications of the ACM, 1975This paper describes a recovery scheme for syntax errors which provides automatically-generated high quality recovery with good diagnostic information at relatively low cost. Previous recovery techniques are summarized and empirical comparisons are made. Suggestions for further research on this topic conclude the paper.
Susan L. Graham
exaly +5 more sources
Low-Power Approximate Unsigned Multipliers With Configurable Error Recovery
IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 2019Approximate circuits have been considered for applications that can tolerate some loss of accuracy with improved performance and/or energy efficiency.
Honglan Jiang +3 more
semanticscholar +1 more source
International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 2019
We aimed at investigating the effects of error recovery strategy that could enable the drivers to recover from the non-understanding error when interacting with the in-vehicle voice user interface (VUI).
Jihyun Kim, Meuel Jeong, S. Lee
semanticscholar +1 more source
We aimed at investigating the effects of error recovery strategy that could enable the drivers to recover from the non-understanding error when interacting with the in-vehicle voice user interface (VUI).
Jihyun Kim, Meuel Jeong, S. Lee
semanticscholar +1 more source
ACM Symposium on User Interface Software and Technology, 2021
Existing approaches to trading off false positive versus false negative errors in input recognition are based on imprecise ideas of how these errors affect user experience that are unlikely to hold for all situations.
Ben Lafreniere +7 more
semanticscholar +1 more source
Existing approaches to trading off false positive versus false negative errors in input recognition are based on imprecise ideas of how these errors affect user experience that are unlikely to hold for all situations.
Ben Lafreniere +7 more
semanticscholar +1 more source
2000
This paper highlights the positive role that human operators often play in preventing small failures and errors from developing into an actual system breakdown. The resulting ‘near misses’ may provide an insight into a powerful alternative to human error prevention, namely: human recovery promotion.
Schaaf, van der, T.W., Kanse, L.
openaire +2 more sources
This paper highlights the positive role that human operators often play in preventing small failures and errors from developing into an actual system breakdown. The resulting ‘near misses’ may provide an insight into a powerful alternative to human error prevention, namely: human recovery promotion.
Schaaf, van der, T.W., Kanse, L.
openaire +2 more sources
Remnant error concealment technique for error recovery
Proceedings Second International Workshop on Digital and Computational Video, 2002This paper presents a remnant error concealment (REC) technique based on generic error concealment (GEC). Two most common issues in video error recovery systems are the locations of lost blocks and error recovery techniques. By using a multistage error detection algorithm to obtain the location of lost blocks of random bit error in the MPEG-2 bit ...
Hung-Sheng Wong +2 more
openaire +2 more sources
Just-In-Time Checkpointing: Low Cost Error Recovery from Deep Learning Training Failures
European Conference on Computer SystemsDeep Learning training jobs process large amounts of training data using many GPU devices, often running for weeks or months. When hardware or software failures happen, these jobs need to restart, losing the memory state for the Deep Neural Network (DNN)
Tanmaey Gupta +7 more
semanticscholar +1 more source