default search action
Min Chi
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j16]Preya Shabrina, Behrooz Mostafavi, Mark Abdelshiheed, Min Chi, Tiffany Barnes:
Investigating the Impact of Backward Strategy Learning in a Logic Tutor: Aiding Subgoal Learning Towards Improved Problem Solving. Int. J. Artif. Intell. Educ. 34(3): 825-861 (2024) - [j15]Mark Abdelshiheed, Tiffany Barnes, Min Chi:
How and When: The Impact of Metacognitive Knowledge Instruction and Motivation on Transfer Across Intelligent Tutoring Systems. Int. J. Artif. Intell. Educ. 34(3): 974-1007 (2024) - [c117]Ge Gao, Xi Yang, Min Chi:
Get a Head Start: On-Demand Pedagogical Policy Selection in Intelligent Tutoring. AAAI 2024: 12136-12144 - [c116]Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price:
Evaluating Multi-Knowledge Component Interpretability of Deep Knowledge Tracing Models in Programming. EDM 2024 - [c115]Nazia Alam, Behrooz Mostafavi, Sutapa Dey Tithi, Min Chi, Tiffany Barnes:
How Much Training is Needed? Reducing Training Time using Deep Reinforcement Learning in an Intelligent Tutor. EDM 2024 - [c114]Md Mirajul Islam, Xi Yang, John Wesley Hostetter, Adittya Soukarjya Saha, Min Chi:
A Generalized Apprenticeship Learning Framework for Modeling Heterogeneous Student Pedagogical Strategies. EDM 2024 - [c113]Gyuhun Jung, Markel Sanz Ausin, Tiffany Barnes, Min Chi:
More, May not the Better: Insights from Applying Deep Reinforcement Learning for Pedagogical Policy Induction. EDM 2024 - [c112]Ge Gao, Qitong Gao, Xi Yang, Song Ju, Miroslav Pajic, Min Chi:
On Trajectory Augmentations for Off-Policy Evaluation. ICLR 2024 - [c111]Hyunwoo Sohn, Kyungjin Park, Baekkwan Park, Min Chi:
Multi-TA: Multilevel Temporal Augmentation for Robust Septic Shock Early Prediction. IJCAI 2024: 6035-6043 - [i26]Md Mirajul Islam, Xi Yang, John Wesley Hostetter, Adittya Soukarjya Saha, Min Chi:
A Generalized Apprenticeship Learning Framework for Modeling Heterogeneous Student Pedagogical Strategies. CoRR abs/2406.02450 (2024) - [i25]Ge Gao, Xi Yang, Qitong Gao, Song Ju, Miroslav Pajic, Min Chi:
Off-Policy Selection for Initiating Human-Centric Experimental Design. CoRR abs/2410.20017 (2024) - 2023
- [j14]Markel Sanz Ausin, Mehak Maniktala, Tiffany Barnes, Min Chi:
The Impact of Batch Deep Reinforcement Learning on Student Performance: A Simple Act of Explanation Can Go A Long Way. Int. J. Artif. Intell. Educ. 33(4): 1031-1056 (2023) - [j13]Yeo Jin Kim, Min Chi:
Time-aware deep reinforcement learning with multi-temporal abstraction. Appl. Intell. 53(17): 20007-20033 (2023) - [j12]Munindar P. Singh, Min Chi, Veena Misra:
Healthful Connected Living: Vision and Challenges for the Case of Obesity. IEEE Internet Comput. 27(3): 7-14 (2023) - [j11]Daniel S. Shen, Min Chi:
TC-DTW: Accelerating multivariate dynamic time warping through triangle inequality and point clustering. Inf. Sci. 621: 611-626 (2023) - [j10]Mehak Maniktala, Min Chi, Tiffany Barnes:
Enhancing a student productivity model for adaptive problem-solving assistance. User Model. User Adapt. Interact. 33(1): 159-188 (2023) - [c110]Nazia Alam, Mehak Maniktala, Behrooz Mostafavi, Min Chi, Tiffany Barnes:
Does Knowing When Help Is Needed Improve Subgoal Hint Performance in an Intelligent Data-Driven Logic Tutor? AAAI 2023: 15895-15902 - [c109]Nazia Alam, Behrooz Mostafavi, Min Chi, Tiffany Barnes:
Exploring the Effect of Autoencoder Based Feature Learning for a Deep Reinforcement Learning Policy for Providing Proactive Help. AIED (Posters/Late Breaking Results/...) 2023: 278-283 - [c108]Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes, Min Chi:
Leveraging Deep Reinforcement Learning for Metacognitive Interventions Across Intelligent Tutoring Systems. AIED 2023: 291-303 - [c107]Preya Shabrina, Behrooz Mostafavi, Min Chi, Tiffany Barnes:
Impact of Learning a Subgoal-Directed Problem-Solving Strategy Within an Intelligent Logic Tutor. AIED 2023: 389-400 - [c106]Markel Sanz Ausin, Mark Abdelshiheed, Tiffany Barnes, Min Chi:
A Unified Batch Hierarchical Reinforcement Learning Framework for Pedagogical Policy Induction with Deep Bisimulation Metrics. AIED (Posters/Late Breaking Results/...) 2023: 599-605 - [c105]John Wesley Hostetter, Mark Abdelshiheed, Tiffany Barnes, Min Chi:
A Self-Organizing Neuro-Fuzzy Q-Network: Systematic Design with Offline Hybrid Learning. AAMAS 2023: 1248-1257 - [c104]Ge Gao, Song Ju, Markel Sanz Ausin, Min Chi:
HOPE: Human-Centric Off-Policy Evaluation for E-Learning and Healthcare. AAMAS 2023: 1504-1513 - [c103]Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes, Min Chi:
Bridging Declarative, Procedural, and Conditional Metacognitive Knowledge Gap Using Deep Reinforcement Learning. CogSci 2023 - [c102]Yang Shi, Robin Schmucker, Min Chi, Tiffany Barnes, Thomas W. Price:
KC-Finder: Automated Knowledge Component Discovery for Programming Problems. EDM 2023 - [c101]Preya Shabrina, Behrooz Mostafavi, Sutapa Dey Tithi, Min Chi, Tiffany Barnes:
Learning Problem Decomposition-Recomposition with Data-driven Chunky Parsons Problems within an Intelligent Logic Tutor. EDM 2023 - [c100]John Wesley Hostetter, Mark Abdelshiheed, Tiffany Barnes, Min Chi:
Leveraging Fuzzy Logic Towards More Explainable Reinforcement Learning-Induced Pedagogical Policies on Intelligent Tutoring Systems. FUZZ 2023: 1-7 - [c99]John Wesley Hostetter, Min Chi:
Latent Space Encoding for Interpretable Fuzzy Logic Rules in Continuous and Noisy High-Dimensional Spaces. FUZZ 2023: 1-6 - [c98]Ge Gao, Min Chi:
Trace Augmentation with Missing EHRs for Sepsis Treatments. ICHI 2023: 480 - [c97]Qitong Gao, Ge Gao, Min Chi, Miroslav Pajic:
Variational Latent Branching Model for Off-Policy Evaluation. ICLR 2023 - [c96]Xi Yang, Ge Gao, Min Chi:
Hierarchical Apprenticeship Learning for Disease Progression Modeling. IJCAI 2023: 2388-2396 - [c95]John Wesley Hostetter, Cristina Conati, Xi Yang, Mark Abdelshiheed, Tiffany Barnes, Min Chi:
XAI to Increase the Effectiveness of an Intelligent Pedagogical Agent. IVA 2023: 28:1-28:9 - [c94]Qitong Gao, Ge Gao, Juncheng Dong, Vahid Tarokh, Min Chi, Miroslav Pajic:
Off-Policy Evaluation for Human Feedback. NeurIPS 2023 - [i24]Qitong Gao, Ge Gao, Min Chi, Miroslav Pajic:
Variational Latent Branching Model for Off-Policy Evaluation. CoRR abs/2301.12056 (2023) - [i23]Ge Gao, Song Ju, Markel Sanz Ausin, Min Chi:
HOPE: Human-Centric Off-Policy Evaluation for E-Learning and Healthcare. CoRR abs/2302.09212 (2023) - [i22]Mark Abdelshiheed, Mehak Maniktala, Song Ju, Ayush Jain, Tiffany Barnes, Min Chi:
Preparing Unprepared Students For Future Learning. CoRR abs/2303.11960 (2023) - [i21]Mark Abdelshiheed, John Wesley Hostetter, Preya Shabrina, Tiffany Barnes, Min Chi:
The Power of Nudging: Exploring Three Interventions for Metacognitive Skills Instruction across Intelligent Tutoring Systems. CoRR abs/2303.11965 (2023) - [i20]Mark Abdelshiheed, John Wesley Hostetter, Xi Yang, Tiffany Barnes, Min Chi:
Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer. CoRR abs/2303.12223 (2023) - [i19]Mark Abdelshiheed, Guojing Zhou, Mehak Maniktala, Tiffany Barnes, Min Chi:
Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning. CoRR abs/2303.13541 (2023) - [i18]Mark Abdelshiheed, Mehak Maniktala, Tiffany Barnes, Min Chi:
Assessing Competency Using Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning. CoRR abs/2303.14609 (2023) - [i17]Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes, Min Chi:
Leveraging Deep Reinforcement Learning for Metacognitive Interventions across Intelligent Tutoring Systems. CoRR abs/2304.09821 (2023) - [i16]Mark Abdelshiheed, John Wesley Hostetter, Tiffany Barnes, Min Chi:
Bridging Declarative, Procedural, and Conditional Metacognitive Knowledge Gap Using Deep Reinforcement Learning. CoRR abs/2304.11739 (2023) - [i15]Xi Yang, Ge Gao, Min Chi:
An Offline Time-aware Apprenticeship Learning Framework for Evolving Reward Functions. CoRR abs/2305.09070 (2023) - [i14]Qitong Gao, Ge Gao, Juncheng Dong, Vahid Tarokh, Min Chi, Miroslav Pajic:
Off-Policy Evaluation for Human Feedback. CoRR abs/2310.07123 (2023) - 2022
- [j9]Christa Cody, Mehak Maniktala, Nicholas Lytle, Min Chi, Tiffany Barnes:
The Impact of Looking Further Ahead: A Comparison of Two Data-driven Unsolicited Hint Types on Performance in an Intelligent Data-driven Logic Tutor. Int. J. Artif. Intell. Educ. 32(2): 263-296 (2022) - [j8]Guojing Zhou, Hamoon Azizsoltani, Markel Sanz Ausin, Tiffany Barnes, Min Chi:
Leveraging Granularity: Hierarchical Reinforcement Learning for Pedagogical Policy Induction. Int. J. Artif. Intell. Educ. 32(2): 454-500 (2022) - [c93]Ye Mao, Farzaneh Khoshnevisan, Thomas W. Price, Tiffany Barnes, Min Chi:
Cross-Lingual Adversarial Domain Adaptation for Novice Programming. AAAI 2022: 7682-7690 - [c92]Song Ju, Xi Yang, Tiffany Barnes, Min Chi:
Student-Tutor Mixed-Initiative Decision-Making Supported by Deep Reinforcement Learning. AIED (1) 2022: 440-452 - [c91]Mark Abdelshiheed, John Wesley Hostetter, Xi Yang, Tiffany Barnes, Min Chi:
Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer. AIED (1) 2022: 546-552 - [c90]Mark Abdelshiheed, John Wesley Hostetter, Preya Shabrina, Tiffany Barnes, Min Chi:
The Power of Nudging: Exploring Three Interventions for Metacognitive Skills Instruction across Intelligent Tutoring Systems. CogSci 2022 - [c89]Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price:
Code-DKT: A Code-based Knowledge Tracing Model for Programming Tasks. EDM 2022 - [c88]Ge Gao, Farzaneh Khoshnevisan, Min Chi:
Reconstructing Missing EHRs Using Time-Aware Within- and Cross-Visit Information for Septic Shock Early Prediction. ICHI 2022: 151-162 - [c87]Ge Gao, Qitong Gao, Xi Yang, Miroslav Pajic, Min Chi:
A Reinforcement Learning-Informed Pattern Mining Framework for Multivariate Time Series Classification. IJCAI 2022: 2994-3000 - [i13]Mitchell Plyler, Michael Green, Min Chi:
Making a (Counterfactual) Difference One Rationale at a Time. CoRR abs/2201.05177 (2022) - [i12]Ge Gao, Farzaneh Khoshnevisan, Min Chi:
Reconstructing Missing EHRs Using Time-Aware Within- and Cross-Visit Information for Septic Shock Early Prediction. CoRR abs/2203.08245 (2022) - [i11]Yang Shi, Min Chi, Tiffany Barnes, Thomas W. Price:
Code-DKT: A Code-based Knowledge Tracing Model for Programming Tasks. CoRR abs/2206.03545 (2022) - [i10]Mehak Maniktala, Min Chi, Tiffany Barnes:
Enhancing a Student Productivity Model for Adaptive Problem-Solving Assistance. CoRR abs/2207.03025 (2022) - [i9]Preya Shabrina, Behrooz Mostafavi, Mark Abdelshiheed, Min Chi, Tiffany Barnes:
Investigating the Impact of Backward Strategy Learning in a Logic Tutor: Aiding Subgoal Learning towards Improved Problem Solving. CoRR abs/2208.04696 (2022) - [i8]Preya Shabrina, Samiha Marwan, Andrew Bennison, Min Chi, Thomas W. Price, Tiffany Barnes:
A Multicriteria Evaluation for Data-Driven Programming Feedback Systems: Accuracy, Effectiveness, Fallibility, and Students' Response. CoRR abs/2208.05326 (2022) - 2021
- [j7]Mehak Maniktala, Christa Cody, Tiffany Barnes, Min Chi:
Correction to: Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor. Int. J. Artif. Intell. Educ. 31(1): 154-155 (2021) - [c86]Song Ju, Guojing Zhou, Mark Abdelshiheed, Tiffany Barnes, Min Chi:
Evaluating Critical Reinforcement Learning Framework in the Field. AIED (1) 2021: 215-227 - [c85]Markel Sanz Ausin, Mehak Maniktala, Tiffany Barnes, Min Chi:
Tackling the Credit Assignment Problem in Reinforcement Learning-Induced Pedagogical Policies with Neural Networks. AIED (1) 2021: 356-368 - [c84]Markel Sanz Ausin, Hamoon Azizsoltani, Song Ju, Yeo-Jin Kim, Min Chi:
InferNet for Delayed Reinforcement Tasks: Addressing the Temporal Credit Assignment Problem. IEEE BigData 2021: 1337-1348 - [c83]Song Ju, Yeo Jin Kim, Markel Sanz Ausin, Maria E. Mayorga, Min Chi:
To Reduce Healthcare Workload: Identify Critical Sepsis Progression Moments through Deep Reinforcement Learning. IEEE BigData 2021: 1640-1646 - [c82]Yeo Jin Kim, Markel Sanz Ausin, Min Chi:
Multi-Temporal Abstraction with Time-Aware Deep Q-Learning for Septic Shock Prevention. IEEE BigData 2021: 1657-1663 - [c81]Mark Abdelshiheed, Mehak Maniktala, Song Ju, Ayush Jain, Tiffany Barnes, Min Chi:
Preparing Unprepared Students For Future Learning. CogSci 2021 - [c80]Yang Shi, Ye Mao, Tiffany Barnes, Min Chi, Thomas W. Price:
More With Less: Exploring How to Use Deep Learning Effectively through Semi-supervised Learning for Automatic Bug Detection in Student Code. EDM 2021 - [c79]Ye Mao, Yang Shi, Samiha Marwan, Thomas W. Price, Tiffany Barnes, Min Chi:
Knowing both when and where: Temporal-ASTNN for Early Prediction of Student Success in Novice Programming Tasks. EDM 2021 - [c78]Samiha Marwan, Yang Shi, Ian Menezes, Min Chi, Tiffany Barnes, Thomas W. Price:
Just a Few Expert Constraints Can Help: Humanizing Data-Driven Subgoal Detection for Novice Programming. EDM 2021 - [c77]Esha Sharma, Lauren B. Davis, Julie S. Ivy, Min Chi:
Data to Donations: Towards In-Kind Food Donation Prediction across Two Coasts. GHTC 2021: 281-288 - [c76]Xi Yang, Yuan Zhang, Min Chi:
Multi-series Time-aware Sequence Partitioning for Disease Progression Modeling. IJCAI 2021: 3581-3587 - [c75]Mitchell Plyler, Michael Green, Min Chi:
Making a (Counterfactual) Difference One Rationale at a Time. NeurIPS 2021: 28701-28713 - [c74]Farzaneh Khoshnevisan, Min Chi:
Unifying Domain Adaptation and Domain Generalization for Robust Prediction Across Minority Racial Groups. ECML/PKDD (1) 2021: 521-537 - [i7]Daniel Shen, Min Chi:
TC-DTW: Accelerating Multivariate Dynamic Time Warping Through Triangle Inequality and Point Clustering. CoRR abs/2101.07731 (2021) - [i6]Christa Cody, Mehak Maniktala, Nicholas Lytle, Min Chi, Tiffany Barnes:
The Impact of Looking Further Ahead: A Comparison of Two Data-driven Unsolicited Hint Types on Performance in an Intelligent Data-driven Logic Tutor. CoRR abs/2102.05741 (2021) - [i5]Markel Sanz Ausin, Hamoon Azizsoltani, Song Ju, Yeo-Jin Kim, Min Chi:
InferNet for Delayed Reinforcement Tasks: Addressing the Temporal Credit Assignment Problem. CoRR abs/2105.00568 (2021) - [i4]Yeo-Jin Kim, Min Chi:
Time-Aware Q-Networks: Resolving Temporal Irregularity for Deep Reinforcement Learning. CoRR abs/2105.02580 (2021) - 2020
- [j6]Mehak Maniktala, Christa Cody, Tiffany Barnes, Min Chi:
Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor. Int. J. Artif. Intell. Educ. 30(4): 637-667 (2020) - [j5]Yuan Zhang, Chen Lin, Min Chi:
Going deeper: Automatic short-answer grading by combining student and question models. User Model. User Adapt. Interact. 30(1): 51-80 (2020) - [c73]Markel Sanz Ausin, Mehak Maniktala, Tiffany Barnes, Min Chi:
Exploring the Impact of Simple Explanations and Agency on Batch Deep Reinforcement Learning Induced Pedagogical Policies. AIED (1) 2020: 472-485 - [c72]Farzaneh Khoshnevisan, Min Chi:
An Adversarial Domain Separation Framework for Septic Shock Early Prediction Across EHR Systems. IEEE BigData 2020: 64-73 - [c71]Hyunwoo Sohn, Kyungjin Park, Min Chi:
MuLan: Multilevel Language-based Representation Learning for Disease Progression Modeling. IEEE BigData 2020: 1246-1255 - [c70]Mark Abdelshiheed, Min Chi:
Metacognition and Motivation: The Role of Time-Awareness in Preparation for Future Learning. CogSci 2020 - [c69]Christa Cody, Mehak Maniktala, David Warren, Min Chi, Tiffany Barnes:
Does autonomy help Help? The impact of unsolicited hints and choice on help avoidance and learning. EDM 2020 - [c68]Song Ju, Min Chi, Guojing Zhou:
Pick the Moment: Identifying Critical Pedagogical Decisions Using Long-Short Term Rewards. EDM 2020 - [c67]Mehak Maniktala, Tiffany Barnes, Min Chi:
Extending the Hint Factory: Towards Modelling Productivity for Open-ended Problem-solving. EDM 2020 - [c66]Ye Mao, Samiha Marwan, Thomas W. Price, Tiffany Barnes, Min Chi:
What Time is It? Student Modeling Needs to Know. EDM 2020 - [c65]Samiha Marwan, Thomas W. Price, Min Chi, Tiffany Barnes:
Immediate Data-Driven Positive Feedback Increases Engagement on Programming Homework for Novices. CSEDM@EDM 2020 - [c64]Preya Shabrina, Samiha Marwan, Min Chi, Thomas W. Price, Tiffany Barnes:
The Impact of Data-driven Positive Programming Feedback: When it Helps, What Happens when it Goes Wrong, and How Students Respond. CSEDM@EDM 2020 - [c63]Xi Yang, Guojing Zhou, Michelle Taub, Roger Azevedo, Min Chi:
Student Subtyping via EM-Inverse Reinforcement Learning. EDM 2020 - [c62]Guojing Zhou, Hamoon Azizsoltani, Markel Sanz Ausin, Tiffany Barnes, Min Chi:
Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract). IJCAI 2020: 4691-4695 - [c61]Xi Yang, Yeo-Jin Kim, Michelle Taub, Roger Azevedo, Min Chi:
PRIME: Block-Wise Missingness Handling for Multi-modalities in Intelligent Tutoring Systems. MMM (2) 2020: 63-75 - [c60]Guojing Zhou, Xi Yang, Hamoon Azizsoltani, Tiffany Barnes, Min Chi:
Improving Student-System Interaction Through Data-driven Explanations of Hierarchical Reinforcement Learning Induced Pedagogical Policies. UMAP 2020: 284-292 - [i3]Mehak Maniktala, Christa Cody, Tiffany Barnes, Min Chi:
Avoiding Help Avoidance: Using Interface Design Changes to Promote Unsolicited Hint Usage in an Intelligent Tutor. CoRR abs/2009.13371 (2020) - [i2]Mehak Maniktala, Christa Cody, Amy Isvik, Nicholas Lytle, Min Chi, Tiffany Barnes:
Extending the Hint Factory for the assistance dilemma: A novel, data-driven HelpNeed Predictor for proactive problem-solving help. CoRR abs/2010.04124 (2020) - [i1]Farzaneh Khoshnevisan, Min Chi:
An Adversarial Domain Separation Framework for Septic Shock Early Prediction Across EHR Systems. CoRR abs/2010.13952 (2020)
2010 – 2019
- 2019
- [c59]Guojing Zhou, Hamoon Azizsoltani, Markel Sanz Ausin, Tiffany Barnes, Min Chi:
Hierarchical Reinforcement Learning for Pedagogical Policy Induction. AIED (1) 2019: 544-556 - [c58]Ali Jazayeri, Muge Capan, Christopher C. Yang, Farzaneh Khoshnevisan, Min Chi, Ryan Arnold:
Network-Based Modeling of Sepsis: Quantification and Evaluation of Simultaneity of Organ Dysfunctions. BCB 2019: 87-96 - [c57]Chen Lin, Julie S. Ivy, Min Chi:
Multi-layer Facial Representation Learning for Early Prediction of Septic Shock. IEEE BigData 2019: 840-849 - [c56]Shuai Yang, Xipeng Shen, Min Chi:
Streamline Density Peak Clustering for Practical Adoptions. CIKM 2019: 49-58 - [c55]Guojing Zhou, Xi Yang, Min Chi:
Big, Little, or Both? Exploring the Impact of Granularity on Learning for Students with Different Incoming Competence. CogSci 2019: 3206-3212 - [c54]Markel Sanz Ausin, Hamoon Azizsoltani, Tiffany Barnes, Min Chi:
Leveraging Deep Reinforcement Learning for Pedagogical Policy Induction in an Intelligent Tutoring System. EDM 2019 - [c53]Song Ju, Shitian Shen, Hamoon Azizsoltani, Tiffany Barnes, Min Chi:
Importance Sampling to Identify Empirically Valid Policies and their Critical Decisions. EDM (Workshops) 2019: 69-78 - [c52]Song Ju, Guojing Zhou, Hamoon Azizsoltani, Tiffany Barnes, Min Chi:
Identifying Critical Pedagogical Decisions through Adversarial Deep Reinforcement Learning. EDM 2019 - [c51]Ye Mao, Rui Zhi, Farzaneh Khoshnevisan, Thomas W. Price, Tiffany Barnes, Min Chi:
One minute is enough: Early Prediction of Student Success and Event-level Difficulty during Novice Programming Tasks. EDM 2019 - [c50]Rui Zhi, Min Chi, Tiffany Barnes, Thomas W. Price:
Evaluating the Effectiveness of Parsons Problems for Block-based Programming. ICER 2019: 51-59 - [c49]Xi Yang, Yeo-Jin Kim, Farzaneh Khoshnevisan, Yuan Zhang, Min Chi:
Missing Data Imputation for MIMIC-III using Matrix Decomposition. ICHI 2019: 1-3 - [c48]Yuan Zhang, Xi Yang, Julie S. Ivy, Min Chi:
Time-aware Adversarial Networks for Adapting Disease Progression Modeling. ICHI 2019: 1-11 - [c47]Hamoon Azizsoltani, Yeo-Jin Kim, Markel Sanz Ausin, Tiffany Barnes, Min Chi:
Unobserved Is Not Equal to Non-existent: Using Gaussian Processes to Infer Immediate Rewards Across Contexts. IJCAI 2019: 1974-1980 - [c46]Yuan Zhang, Xi Yang, Julie S. Ivy, Min Chi:
ATTAIN: Attention-based Time-Aware LSTM Networks for Disease Progression Modeling. IJCAI 2019: 4369-4375 - [c45]Daniel Shen, Min Chi:
An Initial Study on Adapting DTW at Individual Query for Electrocardiogram Analysis. AALTD@PKDD/ECML 2019: 213-228 - [c44]Rui Zhi, Thomas W. Price, Samiha Marwan, Alexandra Milliken, Tiffany Barnes, Min Chi:
Exploring the Impact of Worked Examples in a Novice Programming Environment. SIGCSE 2019: 98-104 - 2018
- [c43]Shitian Shen, Behrooz Mostafavi, Collin F. Lynch, Tiffany Barnes, Min Chi:
Empirically Evaluating the Effectiveness of POMDP vs. MDP Towards the Pedagogical Strategies Induction. AIED (2) 2018: 327-331 - [c42]Xi Yang, Yuan Zhang, Min Chi:
Time-aware Subgroup Matrix Decomposition: Imputing Missing Data Using Forecasting Events. IEEE BigData 2018: 1524-1533 - [c41]Chen Lin, Yuan Zhang, Julie S. Ivy, Muge Capan, Ryan Arnold, Jeanne M. Huddleston, Min Chi:
Early Diagnosis and Prediction of Sepsis Shock by Combining Static and Dynamic Information Using Convolutional-LSTM. ICHI 2018: 219-228 - [c40]Farzaneh Khoshnevisan, Julie S. Ivy, Muge Capan, Ryan Arnold, Jeanne Huddleston, Min Chi:
Recent Temporal Pattern Mining for Septic Shock Early Prediction. ICHI 2018: 229-240 - [c39]Yeo-Jin Kim, Min Chi:
Temporal Belief Memory: Imputing Missing Data during RNN Training. IJCAI 2018: 2326-2332 - [c38]Shitian Shen, Markel Sanz Ausin, Behrooz Mostafavi, Min Chi:
Improving Learning & Reducing Time: A Constrained Action-Based Reinforcement Learning Approach. UMAP 2018: 43-51 - 2017
- [j4]