default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDJin Tian 0001
Person information
- affiliation: Iowa State University, Department of Computer Science, Ames, IA, USA
- affiliation: University of California, Los Angeles, Computer Science Department, CA, USA
Other persons with the same name
- Jin Tian — disambiguation page
- Jin Tian 0002 — Beihang University, School of Reliability and Systems Engineering, Beijing, China
- Jin Tian 0003 — Jinling Institute of Technology, School of Networks and Telecommunications, Nanjing, China
- Jin Tian 0004 — Shanghai University Of Engineering Science, College of Electronic and Electrical Engineering, China
- Jin Tian 0005 — Tianjin University, College of Management and Economics, China
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2023
[c51]Tara V. Anand, Adèle H. Ribeiro
, Jin Tian, Elias Bareinboim:
Causal Effect Identification in Cluster DAGs. AAAI 2023: 12172-12179- [c50]Yonghan Jung, Jin Tian, Elias Bareinboim:
Estimating Joint Treatment Effects by Combining Multiple Experiments. ICML 2023: 15451-15527 - [c49]Yonghan Jung, Ivan Diaz, Jin Tian, Elias Bareinboim:
Estimating Causal Effects Identifiable from a Combination of Observations and Experiments. NeurIPS 2023 - [i24]Hebi Li, Forrest Sheng Bao, Qi Xiao, Jin Tian:
Codepod: A Namespace-Aware, Hierarchical Jupyter for Interactive Development at Scale. CoRR abs/2301.02410 (2023) - 2022
- [c48]Qi Xiao, Hebi Li, Jin Tian, Zhengdao Wang:
Group-Wise Feature Selection for Supervised Learning. ICASSP 2022: 3149-3153 - [c47]Yonghan Jung, Shiva Prasad Kasiviswanathan, Jin Tian, Dominik Janzing, Patrick Blöbaum, Elias Bareinboim:
On Measuring Causal Contributions via do-interventions. ICML 2022: 10476-10501 - [c46]Junzhe Zhang, Jin Tian, Elias Bareinboim:
Partial Counterfactual Identification from Observational and Experimental Data. ICML 2022: 26548-26558 - [c45]Hyunchai Jeong, Jin Tian, Elias Bareinboim:
Finding and Listing Front-door Adjustment Sets. NeurIPS 2022 - [c44]Youbiao He, Hebi Li, Jin Tian, Forrest Sheng Bao:
Circuit Routing Using Monte Carlo Tree Search and Deep Reinforcement Learning. VLSI-DAT 2022: 1-5 - [p1]Elias Bareinboim, Jin Tian, Judea Pearl:
Recovering from Selection Bias in Causal and Statistical Inference. Probabilistic and Causal Inference 2022: 433-450 - [i23]Tara V. Anand, Adèle H. Ribeiro, Jin Tian, Elias Bareinboim:
Effect Identification in Cluster Causal Diagrams. CoRR abs/2202.12263 (2022) - [i22]Hyunchai Jeong, Jin Tian, Elias Bareinboim:
Finding and Listing Front-door Adjustment Sets. CoRR abs/2210.05816 (2022) - 2021
- [c43]Yonghan Jung, Jin Tian, Elias Bareinboim:
Estimating Identifiable Causal Effects through Double Machine Learning. AAAI 2021: 12113-12122 - [c42]Hebi Li, Youbiao He, Qi Xiao, Jin Tian, Forrest Sheng Bao:
BHDL: A Lucid, Expressive, and Embedded Programming Language and System for PCB Designs. DAC 2021: 355-360 - [c41]Eliska Kloberdanz, Jin Tian, Wei Le:
An Improved (Adversarial) Reprogramming Technique for Neural Networks. ICANN (1) 2021: 3-15 - [c40]Yonghan Jung, Jin Tian, Elias Bareinboim:
Estimating Identifiable Causal Effects on Markov Equivalence Class through Double Machine Learning. ICML 2021: 5168-5179 - [c39]Yonghan Jung, Jin Tian, Elias Bareinboim:
Double Machine Learning Density Estimation for Local Treatment Effects with Instruments. NeurIPS 2021: 21821-21833 - [c38]Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian, Jia Liu:
Data Poisoning Attacks and Defenses to Crowdsourcing Systems. WWW 2021: 969-980 - [i21]Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian, Jia Liu:
Data Poisoning Attacks and Defenses to Crowdsourcing Systems. CoRR abs/2102.09171 (2021) - [i20]Junzhe Zhang, Jin Tian, Elias Bareinboim:
Partial Counterfactual Identification from Observational and Experimental Data. CoRR abs/2110.05690 (2021) - 2020
- [c37]Yonghan Jung, Jin Tian, Elias Bareinboim:
Estimating Causal Effects Using Weighting-Based Estimators. AAAI 2020: 10186-10193 - [c36]Yonghan Jung, Jin Tian, Elias Bareinboim:
Learning Causal Effects via Weighted Empirical Risk Minimization. NeurIPS 2020 - [i19]Hebi Li, Qi Xiao, Jin Tian:
Supervised Whole DAG Causal Discovery. CoRR abs/2006.04697 (2020)
2010 – 2019
- 2019
- [j6]Ki-sung Koo, Manimaran Govindarasu, Jin Tian:
Event prediction algorithm using neural networks for the power management system of electric vehicles. Appl. Soft Comput. 84 (2019) - [c35]Juan D. Correa, Jin Tian, Elias Bareinboim:
Identification of Causal Effects in the Presence of Selection Bias. AAAI 2019: 2744-2751 - [c34]Juan D. Correa, Jin Tian, Elias Bareinboim:
Adjustment Criteria for Generalizing Experimental Findings. ICML 2019: 1361-1369 - [c33]Mojdeh Saadati, Jin Tian:
Adjustment Criteria for Recovering Causal Effects from Missing Data. ECML/PKDD (1) 2019: 561-577 - [i18]Hebi Li, Qi Xiao, Shixin Tian, Jin Tian:
Purifying Adversarial Perturbation with Adversarially Trained Auto-encoders. CoRR abs/1905.10729 (2019) - [i17]Mojdeh Saadati, Jin Tian:
Adjustment Criteria for Recovering Causal Effects from Missing Data. CoRR abs/1907.01654 (2019) - 2018
- [c32]Juan D. Correa, Jin Tian, Elias Bareinboim:
Generalized Adjustment Under Confounding and Selection Biases. AAAI 2018: 6335-6342 - 2017
- [j5]Yanpeng Zhao, Yetian Chen, Kewei Tu, Jin Tian:
Learning Bayesian network structures under incremental construction curricula. Neurocomputing 258: 30-40 (2017) - [c31]Jin Tian:
Recovering Probability Distributions from Missing Data. ACML 2017: 574-589 - 2016
- [j4]Ru He, Jin Tian, Huaiqing Wu:
Structure Learning in Bayesian Networks of a Moderate Size by Efficient Sampling. J. Mach. Learn. Res. 17: 101:1-101:54 (2016) - [c30]Yetian Chen, José P. González-Brenes, Jin Tian:
Joint Discovery of Skill Prerequisite Graphs and Student Models. EDM 2016: 46-53 - [i16]Jin Tian:
Recoverability of Joint Distribution from Missing Data. CoRR abs/1611.04709 (2016) - 2015
- [c29]Elias Bareinboim, Jin Tian:
Recovering Causal Effects from Selection Bias. AAAI 2015: 3475-3481 - [c28]Yanpeng Zhao, Yetian Chen, Kewei Tu, Jin Tian:
Curriculum Learning of Bayesian Network Structures. ACML 2015: 269-284 - [c27]Yetian Chen, Lingjian Meng, Jin Tian:
Exact Bayesian Learning of Ancestor Relations in Bayesian Networks. AISTATS 2015 - [c26]Jin Tian:
Missing at Random in Graphical Models. AISTATS 2015 - [i15]Ru He, Jin Tian, Huaiqing Wu:
Structure Learning in Bayesian Networks of Moderate Size by Efficient Sampling. CoRR abs/1501.04370 (2015) - 2014
- [c25]Elias Bareinboim, Jin Tian, Judea Pearl:
Recovering from Selection Bias in Causal and Statistical Inference. AAAI 2014: 2410-2416 - [c24]Bryant Chen, Jin Tian, Judea Pearl:
Testable Implications of Linear Structural Equation Models. AAAI 2014: 2424-2430 - [c23]Yetian Chen, Jin Tian:
Finding the k-best Equivalence Classes of Bayesian Network Structures for Model Averaging. AAAI 2014: 2431-2438 - [i14]Yetian Chen, Jin Tian, Olga Nikolova, Srinivas Aluru:
A Parallel Algorithm for Exact Bayesian Structure Discovery in Bayesian Networks. CoRR abs/1408.1664 (2014) - 2013
- [j3]Ru He, Jiong Wang, Jin Tian, Cheng-Tao Chu, Bradley Mauney, Igor Perisic:
Session analysis of people search within a professional social network. J. Assoc. Inf. Sci. Technol. 64(5): 929-950 (2013) - [c22]Karthika Mohan, Judea Pearl, Jin Tian:
Graphical Models for Inference with Missing Data. NIPS 2013: 1277-1285 - [i13]Jin Tian, Judea Pearl:
On the Testable Implications of Causal Models with Hidden Variables. CoRR abs/1301.0608 (2013) - [i12]Jin Tian, Judea Pearl:
Causal Discovery from Changes. CoRR abs/1301.2312 (2013) - [i11]Jin Tian:
A Branch-and-Bound Algorithm for MDL Learning Bayesian Networks. CoRR abs/1301.3897 (2013) - [i10]Jin Tian, Judea Pearl:
Probabilities of Causation: Bounds and Identification. CoRR abs/1301.3898 (2013) - 2012
- [i9]Jin Tian, Ru He, Lavanya Ram:
Bayesian Model Averaging Using the k-best Bayesian Network Structures. CoRR abs/1203.3520 (2012) - [i8]Jin Tian, Ru He:
Computing Posterior Probabilities of Structural Features in Bayesian Networks. CoRR abs/1205.2612 (2012) - [i7]Jin Tian:
Identifying Dynamic Sequential Plans. CoRR abs/1206.3292 (2012) - [i6]Changsung Kang, Jin Tian:
Polynomial Constraints in Causal Bayesian Networks. CoRR abs/1206.5275 (2012) - [i5]Jin Tian:
A Criterion for Parameter Identification in Structural Equation Models. CoRR abs/1206.5289 (2012) - [i4]Changsung Kang, Jin Tian:
Inequality Constraints in Causal Models with Hidden Variables. CoRR abs/1206.6829 (2012) - [i3]Changsung Kang, Jin Tian:
Local Markov Property for Models Satisfying Composition Axiom. CoRR abs/1207.1378 (2012) - [i2]Jin Tian:
Generating Markov Equivalent Maximal Ancestral Graphs by Single Edge Replacement. CoRR abs/1207.1428 (2012) - [i1]Jin Tian:
Identifying Conditional Causal Effects. CoRR abs/1207.4161 (2012) - 2010
- [c21]Jin Tian, Ru He, Lavanya Ram:
Bayesian Model Averaging Using the k-best Bayesian Network Structures. UAI 2010: 589-597
2000 – 2009
- 2009
- [j2]Changsung Kang, Jin Tian:
Markov Properties for Linear Causal Models with Correlated Errors. J. Mach. Learn. Res. 10: 41-70 (2009) - [c20]Jin Tian:
Parameter Identification in a Class of Linear Structural Equation Models. IJCAI 2009: 1970-1975 - [c19]Jin Tian, Ru He:
Computing Posterior Probabilities of Structural Features in Bayesian Networks. UAI 2009: 538-547 - 2008
- [c18]Jin Tian:
Identifying Dynamic Sequential Plans. UAI 2008: 554-561 - 2007
- [c17]Jin Tian:
On the Identification of a Class of Linear Models. AAAI 2007: 1284-1289 - [c16]Changsung Kang, Jin Tian:
Polynomial Constraints in Causal Bayesian Networks. UAI 2007: 200-208 - [c15]Jin Tian:
A Criterion for Parameter Identification in Structural Equation Models. UAI 2007: 392-399 - 2006
- [c14]Jin Tian, Changsung Kang, Judea Pearl:
A Characterization of Interventional Distributions in Semi-Markovian Causal Models. AAAI 2006: 1239-1244 - [c13]Changsung Kang, Jin Tian:
A Hybrid Generative/Discriminative Bayesian Classifier. FLAIRS 2006: 562-567 - [c12]Changsung Kang, Jin Tian:
Inequality Constraints in Causal Models with Hidden Variables. UAI 2006 - 2005
- [c11]Jin Tian:
Identifying Direct Causal Effects in Linear Models. AAAI 2005: 346-353 - [c10]Changsung Kang, Jin Tian:
Local Markov Property for Models Satisfying Composition Axiom. UAI 2005: 284-291 - [c9]Jin Tian:
Generating Markov Equivalent Maximal Ancestral Graphs by Single Edge Replacement. UAI 2005: 591-598 - 2004
- [c8]Jin Tian:
Identifying Linear Causal Effects. AAAI 2004: 104-111 - [c7]Jin Tian:
Identifying Conditional Causal Effects. UAI 2004: 561-568 - 2002
- [c6]Jin Tian, Judea Pearl:
A General Identification Condition for Causal Effects. AAAI/IAAI 2002: 567-573 - [c5]Jin Tian, Judea Pearl:
A New Characterization of the Experimental Implications of Causal Bayesian Networks. AAAI/IAAI 2002: 574-580 - [c4]Jin Tian, Judea Pearl:
On the Testable Implications of Causal Models with Hidden Variables. UAI 2002: 519-527 - 2001
- [c3]Jin Tian, Judea Pearl:
Causal Discovery from Changes. UAI 2001: 512-521 - 2000
- [j1]Jin Tian, Judea Pearl:
Probabilities of causation: Bounds and identification. Ann. Math. Artif. Intell. 28(1-4): 287-313 (2000) - [c2]Jin Tian:
A Branch-and-Bound Algorithm for MDL Learning Bayesian Networks. UAI 2000: 580-588 - [c1]Jin Tian, Judea Pearl:
Probabilities of Causation: Bounds and Identification. UAI 2000: 589-598
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-13 00:43 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
