Peer review notice: in addition to peer-reviewed journals, I publish
papers at machine learning conferences such as ICML and NIPS, which
have double-blind peer reviews, and only accept about 20% of
submitted papers.
Reproducible Research notice: a “Reproducible” link for each paper below
provides source code and data that I used to perform the analysis and make
the figures/tables.
Software notice: a “Software” link for each paper below provides a software
package with a reference implementation of the algorithms described
in our paper.
Why does functional pruning yield such fast algorithms for optimal
changepoint detection? Invited talk for TRIPODS seminar
video,
slides,
IEEE NJACS, ASU West ML
Day.
Hocking TD, Khare A. Learning penalty functions for changepoint
detection using elastic-net regularized accelerated failure time
models. In preparation, Software,
Reproducible.
Rust K, Hocking TD. A Log-linear Gradient Descent Algorithm for
Unbalanced Binary Classification using the All Pairs Squared Hinge
Loss. Preprint arXiv:2302.11062.
Hocking TD. Exact line search for Area Under the Minimum with a
margin parameter.
Hocking TD. Finite Sample Complexity Analysis of Binary Segmentation.
Hocking TD. Comparing binsegRcpp with other implementations of
binary segmentation for changepoint detection.
Hocking TD, Jenson R. Predictive Modeling Framework for District
Continuous Improvement.
Hocking TD. Teaching Hidden Markov Models Using Interactive Data
Visualization. Under review at ICER.
Harshe K, Williams J, Hocking TD, Lerner Z. Predicting Neuromuscular
Engagement to Improve Gait Training with a Robotic Ankle
Exoskeleton. Under review at IEEE Robotics and Automation Letters.
Tao F, Huang Y, Hungate BA, Manzoni S, Frey SD, Schmidt MWI,
Reichstein M, Carvalhais N, Ciais P, Jiang L, Lehmann J, Mishra U,
Hugelius G, Hocking TD, Lu X, Shi Z, Viatkin K, Vargas R,
Yigini Y, Omuto C, Malik AA, Peralta G, Cuevas-Corona R, Di Paolo
LE, Luotto I, Liao C, Liang YS, Saynes VS, Huang X, Luo Y.
Microbial carbon use efficiency promoting global soil carbon
storage. Accepted in Nature.
Barr J, Hocking TD, Morton G, Thatcher T, Shaw P. Classifying
Imbalanced Data with AUM Loss. 2022 Fourth International Conference
on Transdisciplinary AI
(TransAI). IEEE.
Hocking TD, Barr J, Thatcher T. Interpretable linear models for
predicting security vulnerabilities in source code. 2022 Fourth International Conference
on Transdisciplinary AI
(TransAI). IEEE
Barr J, Shaw P, Abu-Khzam FN, Thatcher T, Hocking TD. Graph
Embedding: A Methodological Survey. 2022 Fourth International Conference
on Transdisciplinary AI
(TransAI). IEEE
Mihaljevic JR, Borkovec S, Ratnavale S, Hocking TD, Banister KE,
Eppinger JE, Hepp CM, Doerry E. Rapid simulations of spatially
explicit and stochastic models of infectious disease. Preprint
medRxiv. Biology
Methods &
Protocols
2022, Software.
Hocking TD. Chapter “Introduction to machine learning and neural
networks” for book “Land Carbon Cycle Modeling: Matrix Approach,
Data Assimilation, and Ecological Forecasting” edited by Luo Y,
published by Taylor and Francis, download whole book,
download my chapter,
Reproducible.
Kolla A, Hocking TD, Groce A. RcppDeepState, a simple way to fuzz
test Rcpp Packages. Contributed talk at international useR 2021
conference. Software,
abstract,
video,
blog,
results
Hocking TD. Wide-to-tall data reshaping using regular expressions
and the nc package. R
Journal
(2021), doi:10.32614/RJ-2021-029, Software,
Reproducible.
Abraham A, Prys-Jones T, De Cuyper A, Ridenour C, Hempson G, Hocking
TD, Clauss M, Doughty C. Improved estimation of gut passage time
considerably affects trait-based dispersal models.
Functional Ecology 2021; 35: 860-869.
Fotoohinasab A, Hocking TD, Afghah F. A Graph-constrained
Changepoint Detection Approach for ECG Segmentation. In proceedings
of 42th Annual International Conference of the IEEE Engineering in
Medicine and Biology Society (EMBC 2020), IEEE
Xplore.
Hocking TD, Rigaill G, Fearnhead P, Bourque G. Constrained Dynamic
Programming and Supervised Penalty Learning Algorithms for Peak
Detection in Genomic Data. Journal of Machine Learning Research
21(87):1-40, 2020. JMLR,
Preprint arXiv:1703.03352,
Software,
Reproducible.
Hocking TD, Bourque G. Machine Learning Algorithms for Simultaneous
Supervised Detection of Peaks in Multiple Samples and Cell
Types. Pacific Symposium on Biocomputing (2020)
25:367-378, PDF,
Software.
2019
Hocking TD. Comparing namedCapture with other R packages for regular
expressions.
R Journal
(2019), doi:10.32614/RJ-2019-050
Software,
Reproducible.
Jewell S, Hocking TD, Fearnhead P, Witten D. Fast Nonconvex
Deconvolution of Calcium Imaging Data. Biostatistics (2019), doi:
10.1093/biostatistics/kxy083,
pubmed.
2018
Depuydt P, Koster J, Boeva V, Hocking TD, Speleman F, Schleiermacher
G, De Preter K. Meta-mining of copy number profiles of high-risk
neuroblastoma tumors. Scientific Data (2018).
Alirezaie N, Kernohan KD, Hartley T, Majewski J, Hocking
TD. ClinPred: Prediction Tool to Identify Disease-Relevant
Nonsynonymous Single-Nucleotide Variants. American
Journal of Human Genetics
(2018). doi:10.1016/j.ajhg.2018.08.005AJHG,
Software,
used in dbNSFP.
Sievert C, Cai J, VanderPlas S, Ferris K, Khan FUF, Hocking
TD. Extending ggplot2 for linked and animated web graphics. Journal
of Computational and Graphical Statistics (2018).
doi:10.1080/10618600.2018.1513367.
JCGS,
Software,
Reproducible,
Interactive Figures.
Depuydt P, Boeva V, Hocking TD, Cannoodt R, Ambros IM, Ambros PF,
Asgharzadeh S, Attiyeh EF, Combaret V, Defferrari R, Fischer M, Hero
B, Hogarty MD, Irwin MS, Koster J, Kreissman S, Ladenstein R,
Lapouble E, Laureys G, London WB, Mazzocco K, Nakagawara A, Noguera
R, Ohira M, Park JR, Pötschger U, Theissen J, Tonini GP,
Valteau-Couanet D, Varesio L, Versteeg R, Speleman F, Maris JM,
Schleiermacher G, De Preter K. Genomic Amplifications and Distal 6q
Loss: Novel Markers for Poor Survival in High-risk Neuroblastoma
Patients. Journal of the National Cancer
Institute (2018), DOI:10.1093/jnci/djy022,
JNCI.
Shimada K, Shimada S, Sugimoto K, Nakatochi M, Suguro M, Hirakawa A,
Hocking TD, Takeuchi I, Tokunaga T, Takagi Y, Sakamoto A, Aoki T,
Naoe T, Nakamura S, Hayakawa F, Seto M, Tomita A, Kiyoi
H. Development and analysis of patient-derived xenograft mouse
models in intravascular large B-cell lymphoma.
Leukemia 2016. pubmed.
Chicard M, Boyault S, Colmet-Daage L, Richer W, Gentien D, Pierron
G, Lapouble E, Bellini A, Clement N, Iacono I, Bréjon S, Carrere M,
Reyes C, Hocking TD, Bernard V, Peuchmaur M, Corradini N,
Faure-Conter C, Coze C, Plantaz D, Defachelles A-S, Thebaud E,
Gambart M, Millot F, Valteau-Couanet D, Michon J, Puisieux A,
Delattre O, Combaret V, Schleiermacher G. Genomic copy number
profiling using circulating free tumor DNA highlights heterogeneity
in neuroblastoma. Clinical Cancer
Research 2016. journal.
Maidstone R, Hocking TD, Rigaill G, Fearnhead P. On optimal multiple
changepoint algorithms for large data. Statistics and Computing
(2016). doi:10.1007/s11222-016-9636-3
journal,
Software,
Reproducible.
Animint: Interactive Web-Based Animations Using Ggplot2’s Grammar of
Graphics. VanderPlas SR and Sievert C and Hocking TD. Presentation
at
JSM2015.
2014
Suguro M, Yoshida N, Umino A, Kato H, Tagawa H, Nakagawa M, Fukuhara
N, Karnan S, Takeuchi I, Hocking TD, Arita K, Karube K, Tsuzuki S,
Nakamura S, Kinoshita T, Seto M. Clonal heterogeneity of lymphoid
malignancies correlates with poor prognosis. Cancer Sci. 2014
Jul;105(7):897-904. pubmed.
Hocking TD, Boeva V, Rigaill G, Schleiermacher G, Janoueix-Lerosey
I, Delattre O, Richer W, Bourdeaut F, Suguro M, Seto M, Bach F, Vert
J-P. SegAnnDB: interactive Web-based genomic segmentation.
Bioinformatics (2014) 30 (11):
1539-1546. DOI:10.1093/bioinformatics/btu072
pubmed,
Software,
Reproducible.
2013
Hocking TD, Wutzler T, Ponting K and Grosjean P. Sustainable,
extensible documentation generation using inlinedocs. Journal of
Statistical Software (2013), 54(6), 1-20. DOI:10.18637/jss.v054.i06
journal,
Software,
Reproducible.
Hocking TD, Schleiermacher G, Janoueix-Lerosey I, Boeva V, Cappo J,
Delattre O, Bach F, Vert J-P. Learning smoothing models of copy
number profiles using breakpoint annotations. BMC Bioinfo. 2013,
14:164. DOI:10.1186/1471-2105-14-164
journal,
Software,
Reproducible.
Hocking TD, Rigaill G, Bach F, Vert J-P. Learning sparse penalties
for change-point detection using max-margin interval regression.
International Conference on Machine Learning
(ICML), 2013. PMLR,
video,
Software,
Reproducible.
Hocking TD. Learning algorithms and statistical software, with
applications to bioinformatics. PhD thesis, Ecole Normale Superieure
de Cachan,
France. tel-00906029,
Reproducible.
2011
Hocking TD, Joulin A, Bach F, Vert J-P. Clusterpath: an Algorithm
for Clustering using Convex Fusion Penalties. International
Conference on Machine Learning
(ICML), 2011. pdf,
video.
Software,
Reproducible. Cited
by Genevera Allen who showed interactive visualizations in her
Ihaka lecture.
2010
Gautier M, Hocking TD, Foulley JL. A Bayesian outlier criterion to
detect SNPs under selection in large data sets. PloS ONE 5 (8),
e11913
(2010). journal.
2008
Doyon Y, McCammon JM, Miller JC, Faraji F, Ngo C, Katibah GE, Amora
R, Hocking TD, Zhang L, Rebar EJ, Gregory PD, Urnov FD, Amacher
SL. Heritable targeted gene disruption in zebrafish using designed
zinc-finger nucleases. Nature biotechnology 26 (6), 702-70
(2008). pubmed.