Benjamin M. Marlin
Orcid: 0000-0002-2626-3410Affiliations:
- Department of Computer Science, University of Massachusetts Amherst
According to our database1,
Benjamin M. Marlin
authored at least 97 papers
between 2003 and 2024.
Collaborative distances:
Collaborative distances:
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Online presence:
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on cs.umass.edu
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Bibliography
2024
CoRR, 2024
2023
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Assessing the Impact of Context Inference Error and Partial Observability on RL Methods for Just-In-Time Adaptive Interventions.
Proceedings of the Uncertainty in Artificial Intelligence, 2023
Proceedings of the IEEE Military Communications Conference, 2023
2022
BayesLDM: A Domain-Specific Language for Probabilistic Modeling of Longitudinal Data.
CoRR, 2022
Impact of Parameter Sparsity on Stochastic Gradient MCMC Methods for Bayesian Deep Learning.
CoRR, 2022
Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems, 2022
URSABench: A System for Comprehensive Benchmarking of Bayesian Deep Neural Network Models and Inference methods.
Proceedings of Machine Learning and Systems 2022, 2022
Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022
BayesLDM: A Domain-specific Modeling Language for Probabilistic Modeling of Longitudinal Data.
Proceedings of the IEEE/ACM Conference on Connected Health: Applications, 2022
2021
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021
Towards Transformer-Based Real-Time Object Detection at the Edge: A Benchmarking Study.
Proceedings of the 2021 IEEE Military Communications Conference, 2021
Proceedings of the 2021 IEEE Military Communications Conference, 2021
Optimizing Intelligent Edge-clouds with Partitioning, Compression and Speculative Inference.
Proceedings of the 2021 IEEE Military Communications Conference, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Challenges and Opportunities in Approximate Bayesian Deep Learning for Intelligent IoT Systems.
Proceedings of the Third IEEE International Conference on Cognitive Machine Intelligence, 2021
2020
A Survey on Principles, Models and Methods for Learning from Irregularly Sampled Time Series: From Discretization to Attention and Invariance.
CoRR, 2020
URSABench: Comprehensive Benchmarking of Approximate Bayesian Inference Methods for Deep Neural Networks.
CoRR, 2020
Integrating Physiological Time Series and Clinical Notes with Deep Learning for Improved ICU Mortality Prediction.
CoRR, 2020
Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification.
CoRR, 2020
Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020
Towards Objection Detection Under IoT Resource Constraints: Combining Partitioning, Slicing and Compression.
Proceedings of the AIChallengeIoT@SenSys 2020: Proceedings of the 2nd International Workshop on Challenges in Artificial Intelligence and Machine Learning for Internet of Things, 2020
CLIO: enabling automatic compilation of deep learning pipelines across IoT and cloud.
Proceedings of the MobiCom '20: The 26th Annual International Conference on Mobile Computing and Networking, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
Proceedings of the 2nd IEEE International Conference on Cognitive Machine Intelligence, 2020
2019
CoRR, 2019
Integrating Propositional and Relational Label Side Information for Hierarchical Zero-Shot Image Classification.
CoRR, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications, 2019
Poster Abstract: Investigating Fusion-Based Deep Learning Architectures for Smoking Puff Detection.
Proceedings of the 4th IEEE/ACM International Conference on Connected Health: Applications, 2019
Hierarchical Active Learning for Model Personalization in the Presence of Label Scarcity.
Proceedings of the 16th IEEE International Conference on Wearable and Implantable Body Sensor Networks, 2019
2018
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018
Executing Analytics and Fusion Workloads on Transient Computing Resources in Tactical Environments.
Proceedings of the 2018 IEEE Military Communications Conference, 2018
Proceedings of the 38th IEEE International Conference on Distributed Computing Systems, 2018
2017
IEEE Trans. Image Process., 2017
IEEE Pervasive Comput., 2017
iLid: Low-power Sensing of Fatigue and Drowsiness Measures on a Computational Eyeglass.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017
Learning Tree-Structured Detection Cascades for Heterogeneous Networks of Embedded Devices.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
Learning Shallow Detection Cascades for Wearable Sensor-Based Mobile Health Applications.
CoRR, 2016
Parsing wireless electrocardiogram signals with context free grammar conditional random fields.
Proceedings of the 2016 IEEE Wireless Health, 2016
Proceedings of the 13th International Conference on Principles and Practices of Programming on the Java Platform: Virtual Machines, Languages, and Tools, Lugano, Switzerland, August 29, 2016
Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2016
A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Hierarchical Span-Based Conditional Random Fields for Labeling and Segmenting Events in Wearable Sensor Data Streams.
Proceedings of the 33nd International Conference on Machine Learning, 2016
An Improved Data Representation for Smoking Detection with Wearable Respiration Sensors.
Proceedings of the 2016 IEEE International Conference on Healthcare Informatics, 2016
Domain adaptation methods for improving lab-to-field generalization of cocaine detection using wearable ECG.
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2016
Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications, 2016
2015
J. Am. Medical Informatics Assoc., 2015
Analysis and synthesis of 3D shape families via deep-learned generative models of surfaces.
Comput. Graph. Forum, 2015
Classification of Sparse and Irregularly Sampled Time Series with Mixtures of Expected Gaussian Kernels and Random Features.
Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015
Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments, 2015
Proceedings of the 21st Annual International Conference on Mobile Computing and Networking, 2015
Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015
puffMarker: a multi-sensor approach for pinpointing the timing of first lapse in smoking cessation.
Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2015
2014
Proceedings of the Eighth ACM Conference on Recommender Systems, 2014
Proceedings of the 12th Annual International Conference on Mobile Systems, 2014
Proceedings of the Eye Tracking Research and Applications, 2014
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014
Proceedings of the 5th ACM Conference on Bioinformatics, 2014
2013
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2013
Leveraging graphical models to improve accuracy and reduce privacy risks of mobile sensing.
Proceedings of the 11th Annual International Conference on Mobile Systems, 2013
Practical prediction and prefetch for faster access to applications on mobile phones.
Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2013
Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2013
Proceedings of the AMIA 2013, 2013
Towards Collaborative Filtering Recommender Systems for Tailored Health Communications.
Proceedings of the AMIA 2013, 2013
2012
A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Unsupervised pattern discovery in electronic health care data using probabilistic clustering models.
Proceedings of the ACM International Health Informatics Symposium, 2012
2011
Asymptotic Efficiency of Deterministic Estimators for Discrete Energy-Based Models: Ratio Matching and Pseudolikelihood.
Proceedings of the UAI 2011, 2011
Proceedings of the IJCAI 2011, 2011
Proceedings of the 28th International Conference on Machine Learning, 2011
Proceedings of the 28th International Conference on Machine Learning, 2011
Multiscale Conditional Random Fields for Semi-supervised Labeling and Classification.
Proceedings of the Canadian Conference on Computer and Robot Vision, 2011
2010
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
A tutorial on stochastic approximation algorithms for training Restricted Boltzmann Machines and Deep Belief Nets.
Proceedings of the Information Theory and Applications Workshop, 2010
2009
Proceedings of the 2009 ACM Conference on Recommender Systems, 2009
Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Proceedings of the 26th Annual International Conference on Machine Learning, 2009
2008
2007
Proceedings of the UAI 2007, 2007
2005
Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005
2004
Comput. Geom., 2004
Proceedings of the Machine Learning, 2004
2003
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003