Ahmed K. Farahat

Publication Activity (10 Years)

Years Active: 2009-2023
Publications (10 Years): 28

Top Topics

Key Performance Indicators

Fault Detection

Subset Selection

Top Venues

Knowl. Inf. Syst.

Publications

Nishant Yadav, Mahbubul Alam, Ahmed K. Farahat, Dipanjan Ghosh, Chetan Gupta, Auroop R. Ganguly
CDA: Contrastive-adversarial Domain Adaptation. CoRR (2023)
Xian Yeow Lee, Aman Kumar, Lasitha Vidyaratne, Aniruddha Rajendra Rao, Ahmed K. Farahat, Chetan Gupta
An ensemble of convolution-based methods for fault detection using vibration signals. ICPHM (2023)
Jueming Hu, Haiyan Wang, Hsiu-Khuern Tang, Takuya Kanazawa, Chetan Gupta, Ahmed K. Farahat
Knowledge-enhanced reinforcement learning for multi-machine integrated production and maintenance scheduling. Comput. Ind. Eng. 185 (2023)
Xian Yeow Lee, Lasitha Vidyaratne, Mahbubul Alam, Ahmed K. Farahat, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Chetan Gupta
XDNet: A Few-Shot Meta-Learning Approach for Cross-Domain Visual Inspection. CVPR Workshops (2023)
Qiyao Wang, Ahmed K. Farahat, Chetan Gupta, Shuai Zheng
Deep time series models for scarce data. Neurocomputing 456 (2021)
Dustin Carrión-Ojeda, Mahbubul Alam, Sergio Escalera, Ahmed K. Farahat, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Chetan Gupta, Isabelle Guyon, Joël Roman Ky, Xian Yeow Lee, Xin Liu, Felix Mohr, Manh Hung Nguyen, Emmanuel Pintelas, Stefan Roth, Simone Schaub-Meyer, Haozhe Sun, Ihsan Ullah, Joaquin Vanschoren, Lasitha Vidyaratne, Jiamin Wu, Xiaotian Yin
NeurIPS’22 Cross-Domain MetaDL Challenge: Results and lessons learned. NeurIPS (Competition and Demos) (2021)
Hamed Khorasgani, Ahmed K. Farahat, Chetan Gupta
Data-driven Residual Generation for Early Fault Detection with Limited Data. CoRR (2021)
Qiyao Wang, Ahmed K. Farahat, Chetan Gupta, Shuai Zheng
Deep Time Series Models for Scarce Data. CoRR (2021)
Hamed Khorasgani, Haiyan Wang, Chetan Gupta, Ahmed K. Farahat
An Offline Deep Reinforcement Learning for Maintenance Decision-Making. CoRR (2021)
Lijing Wang, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Ahmed K. Farahat, Mahbubul Alam, Chetan Gupta, Jiangzhuo Chen, Madhav Marathe
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models. NeurIPS (2020)
Lijing Wang, Dipanjan Ghosh, Maria Teresa Gonzalez Diaz, Ahmed K. Farahat, Mahbubul Alam, Chetan Gupta, Jiangzhuo Chen, Madhav Marathe
Wisdom of the Ensemble: Improving Consistency of Deep Learning Models. CoRR (2020)
Qiyao Wang, Ahmed K. Farahat, Chetan Gupta, Haiyan Wang
Health Indicator Forecasting for Improving Remaining Useful Life Estimation. CoRR (2020)
Qiyao Wang, Ahmed K. Farahat, Chetan Gupta, Haiyan Wang
Health Indicator Forecasting for Improving Remaining Useful Life Estimation. ICPHM (2020)
Chetan Gupta, Ahmed K. Farahat
Deep Learning for Industrial AI: Challenges, New Methods and Best Practices. KDD (2020)
Qiyao Wang, Ahmed K. Farahat, Kosta Ristovski, Chetan Gupta, Shuai Zheng
Evaluation of Event Impact on Key Performance Indicators. ICMLA (2019)
Qiyao Wang, Shuai Zheng, Ahmed K. Farahat, Susumu Serita, Chetan Gupta
Remaining Useful Life Estimation Using Functional Data Analysis. ICPHM (2019)
Chi Zhang, Chetan Gupta, Seiji Joichi, Ahmed K. Farahat, Huijuan Shao
Risk-Based Dynamic Pricing via Failure Prediction. ICMLA (2019)
Qiyao Wang, Shuai Zheng, Ahmed K. Farahat, Susumu Serita, Takashi Saeki, Chetan Gupta
Multilayer Perceptron for Sparse Functional Data. IJCNN (2019)
Shuai Zheng, Ahmed K. Farahat, Chetan Gupta
Generative Adversarial Networks for Failure Prediction. ECML/PKDD (3) (2019)
Hamed Khorasgani, Arman Hasanzadeh, Ahmed K. Farahat, Chetan Gupta
Fault Detection and Isolation in Industrial Networks using Graph Convolutional Neural Networks. ICPHM (2019)
Qiyao Wang, Shuai Zheng, Ahmed K. Farahat, Susumu Serita, Chetan Gupta
Remaining Useful Life Estimation Using Functional Data Analysis. CoRR (2019)
Shuai Zheng, Ahmed K. Farahat, Chetan Gupta
Generative Adversarial Networks for Failure Prediction. CoRR (2019)
Qiyao Wang, Ahmed K. Farahat, Kosta Ristovski, Hsiu-Khuern Tang, Susumu Serita, Chetan Gupta
What Maintenance is Worth the Money? A Data-Driven Answer. INDIN (2018)
Karan Aggarwal, Onur Atan, Ahmed K. Farahat, Chi Zhang, Kosta Ristovski, Chetan Gupta
Two Birds with One Network: Unifying Failure Event Prediction and Time-to-failure Modeling. IEEE BigData (2018)
Chi Zhang, Chetan Gupta, Ahmed K. Farahat, Kosta Ristovski, Dipanjan Ghosh
Equipment Health Indicator Learning Using Deep Reinforcement Learning. ECML/PKDD (3) (2018)
Karan Aggarwal, Onur Atan, Ahmed K. Farahat, Chi Zhang, Kosta Ristovski, Chetan Gupta
Two Birds with One Network: Unifying Failure Event Prediction and Time-to-failure Modeling. CoRR (2018)
Shuai Zheng, Kosta Ristovski, Ahmed K. Farahat, Chetan Gupta
Long Short-Term Memory Network for Remaining Useful Life estimation. ICPHM (2017)
Yun-Qian Miao, Ahmed K. Farahat, Mohamed S. Kamel
Detecting emerging and evolving novelties with locally adaptive density ratio estimation. Knowl. Inf. Syst. 49 (3) (2016)
Ahmed K. Farahat, Ahmed Elgohary, Ali Ghodsi, Mohamed S. Kamel
Greedy column subset selection for large-scale data sets. Knowl. Inf. Syst. 45 (1) (2015)
Yun-Qian Miao, Ahmed K. Farahat, Mohamed S. Kamel
Locally Adaptive Density Ratio for Detecting Novelty in Twitter Streams. WWW (Companion Volume) (2015)
Ahmed Elbagoury, Rania Ibrahim, Ahmed K. Farahat, Mohamed S. Kamel, Fakhri Karray
Exemplar-Based Topic Detection in Twitter Streams. ICWSM (2015)
Yun-Qian Miao, Ahmed K. Farahat, Mohamed S. Kamel
Ensemble Kernel Mean Matching. ICDM (2015)
Sepideh Seifzadeh, Ahmed K. Farahat, Mohamed S. Kamel, Fakhri Karray
Short-Text Clustering using Statistical Semantics. WWW (Companion Volume) (2015)
Mehrdad J. Gangeh, Ahmed K. Farahat, Ali Ghodsi, Mohamed S. Kamel
Supervised Dictionary Learning and Sparse Representation-A Review. CoRR (2015)
Ahmed Elgohary, Ahmed K. Farahat, Mohamed S. Kamel, Fakhri Karray
-Means on MapReduce. SDM (2014)
Yun-Qian Miao, Ahmed K. Farahat, Mohamed S. Kamel
Discriminative Density-ratio Estimation. SDM (2014)
Ahmed K. Farahat, Ali Ghodsi, Mohamed S. Kamel
Efficient greedy feature selection for unsupervised learning. Knowl. Inf. Syst. 35 (2) (2013)
Yun-Qian Miao, Ahmed K. Farahat, Mohamed S. Kamel
Auto-Tuning Kernel Mean Matching. ICDM Workshops (2013)
Yun-Qian Miao, Ahmed K. Farahat, Mohamed S. Kamel
Discriminative Density-ratio Estimation. CoRR (2013)
Ahmed Elgohary, Ahmed K. Farahat, Mohamed S. Kamel, Fakhri Karray
Embed and Conquer: Scalable Embeddings for Kernel $k$-Means on MapReduce. CoRR (2013)
Ahmed K. Farahat, Ahmed Elgohary, Ali Ghodsi, Mohamed S. Kamel
Greedy Column Subset Selection for Large-scale Data Sets. CoRR (2013)
Ahmed K. Farahat, Ahmed Elgohary, Ali Ghodsi, Mohamed S. Kamel
Distributed Column Subset Selection on MapReduce. ICDM (2013)
Ahmed K. Farahat, Ali Ghodsi, Mohamed S. Kamel
A Fast Greedy Algorithm for Generalized Column Subset Selection. CoRR (2013)
Ahmed K. Farahat, Mohamed S. Kamel
Statistical semantics for enhancing document clustering. Knowl. Inf. Syst. 28 (2) (2011)
Ahmed K. Farahat, Ali Ghodsi, Mohamed S. Kamel
An Efficient Greedy Method for Unsupervised Feature Selection. ICDM (2011)
Ahmed K. Farahat, Ali Ghodsi, Mohamed S. Kamel
A novel greedy algorithm for Nyström approximation. AISTATS (2011)
Ahmed K. Farahat, Mohamed S. Kamel
Document Clustering Using Semantic Kernels Based on Term-Term Correlations. ICDM Workshops (2009)