Jayant Kalagnanam
10 papers · 2016–2024 · 5 venues · across top CS/AI venues
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Achievements
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π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze πΊοΈ Taxonomy Completionist (27) π Century Club Β· Bronze
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Research topics
Machine Learning
(8)
Learning Types Β· Machine Learning
(5)
Artificial Intelligence
(3)
Data Science & Analytics
(3)
Deep Learning
(3)
Core AI
(3)
Methods
(3)
Optimization & Theory
(3)
Mathematics & Optimization
(2)
Architectures
(2)
Core Methods
(2)
Learning Types Β· Deep Learning
(2)
Optimization
(2)
Computer Vision
(1)
Application Areas
(1)
Keywords
time series forecasting
(3)
foundation model
(2)
mixed integer programming
(2)
unsupervised learning
(2)
anomaly detection
(2)
deep learning
(2)
multivariate time series
(2)
few-shot learning
(1)
semi-supervised learning
(1)
stochastic optimization
(1)
convex optimization
(1)
uncertainty quantification
(1)
transfer learning
(1)
distributed optimization
(1)
zero-shot learning
(1)
alternating minimization
(1)
binary classification
(1)
time series
(1)
asynchronous optimization
(1)
conformal prediction
(1)
Papers
AutoMixer for Improved Multivariate Time-Series Forecasting on Business and IT Observability Data
AAAI 2024
Identifying Homogeneous and Interpretable Groups for Conformal Prediction
UAI 2024
Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series
NeurIPS 2024
AI Model Factory: Scaling AI for Industry 4.0 Applications
AAAI 2023
A Time Series is Worth 64 Words: Long-term Forecasting with Transformers
ICLR 2023
AnomalyKiTS: Anomaly Detection Toolkit for Time Series
AAAI 2022
Interpretable Clustering via Multi-Polytope Machines
AAAI 2022
A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees
NeurIPS 2020
Delay-Adaptive Distributed Stochastic Optimization
AAAI 2020
Change Detection Using Directional Statistics
IJCAI 2016