18 citations · 50 across the 9 of their papers we have counts for
10 papers
An End-to-End Time Series Model for Simultaneous Imputation and Forecast
Trang H. Tran, Lam M. Nguyen, Kyongmin Yeo +4
Time series forecasting using historical data has been an interesting and challenging topic, especially when the data is corrupted by missing values. In many industrial problem, it…
TsSHAP: Robust model agnostic feature-based explainability for time series forecasting
Vikas C. Raykar, Arindam Jati, Sumanta Mukherjee +4
A trustworthy machine learning model should be accurate as well as explainable. Understanding why a model makes a certain decision defines the notion of explainability. While vario…
Efficient Pruning for Machine Learning Under Homomorphic Encryption
Ehud Aharoni, Moran Baruch, Pradip Bose +8
Privacy-preserving machine learning (PPML) solutions are gaining widespread popularity. Among these, many rely on homomorphic encryption (HE) that offers confidentiality of the mod…
AutoAI-TS: AutoAI for Time Series Forecasting
Syed Yousaf Shah, Dhaval Patel, Long Vu +10
A large number of time series forecasting models including traditional statistical models, machine learning models and more recently deep learning have been proposed in the literat…
Efficient Encrypted Inference on Ensembles of Decision Trees
Kanthi Sarpatwar, Karthik Nandakumar, Nalini Ratha +4
Data privacy concerns often prevent the use of cloud-based machine learning services for sensitive personal data. While homomorphic encryption (HE) offers a potential solution by e…
Differentially Private Distributed Data Summarization under Covariate Shift
Kanthi Sarpatwar, Karthikeyan Shanmugam, Venkata Sitaramagiridharganesh Ganapavarapu +2
We envision AI marketplaces to be platforms where consumers, with very less data for a target task, can obtain a relevant model by accessing many private data sources with vast num…
Permissioned Blockchain Technologies for Academic Publishing
Petr Novotny, Qi Zhang, Richard Hull +5
Academic publishing is continuously evolving with the gradual adoption of new technologies. Blockchain is a new technology that promises to change how individuals and organizations…
Trusted Multi-Party Computation and Verifiable Simulations: A Scalable Blockchain Approach
Ravi Kiran Raman, Roman Vaculin, Michael Hind +6
Large-scale computational experiments, often running over weeks and over large datasets, are used extensively in fields such as epidemiology, meteorology, computational biology, an…
Similarity Preserving Representation Learning for Time Series Clustering
Qi Lei, Jinfeng Yi, Roman Vaculin +2
A considerable amount of clustering algorithms take instance-feature matrices as their inputs. As such, they cannot directly analyze time series data due to its temporal nature, us…
Alexandria: Extensible Framework for Rapid Exploration of Social Media
Fenno F. Heath, Richard Hull, Elham Khabiri +3
The Alexandria system under development at IBM Research provides an extensible framework and platform for supporting a variety of big-data analytics and visualizations. The system…