Clusterpath: an Algorithm for Clustering using Convex Fusion Penalties. - Toby Hocking; Jean-Philippe Vert; Francis R. Bach; Armand Joulin (ICML, 2011)

Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression. - Toby Hocking; Guillem Rigaill; Jean-Philippe Vert; Francis R. Bach (ICML (3), 2013)

Learning smoothing models of copy number profiles using breakpoint annotations. - Toby Dylan Hocking; Gudrun Schleiermacher; Isabelle Janoueix-Lerosey; Valentina Boeva; Julie Cappo; Olivier Delattre; Francis R. Bach; Jean-Philippe Vert (BMC Bioinform., 2013)

SegAnnDB: interactive Web-based genomic segmentation. - Toby Dylan Hocking; Valentina Boeva; Guillem Rigaill; Gudrun Schleiermacher; Isabelle Janoueix-Lerosey; Olivier Delattre; Wilfrid Richer; Franck Bourdeaut; Miyuki Suguro; Masao Seto; Francis R. Bach; Jean-Philippe Vert (Bioinform., 2014)

Support vector comparison machines. - Toby Dylan Hocking; Supaporn Spanurattana; Masashi Sugiyama (CoRR, 2014)

PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data. - Toby Hocking; Guillem Rigaill; Guillaume Bourque (ICML, 2015)

Maximum Margin Interval Trees. - Alexandre Drouin; Toby Hocking; François Laviolette (NIPS, 2017)

Optimizing ChIP-seq peak detectors using visual labels and supervised machine learning. - Toby Dylan Hocking; Patricia Goerner-Potvin; Andreanne Morin; Xiaojian Shao; Tomi Pastinen; Guillaume Bourque (Bioinform., 2017)

On optimal multiple changepoint algorithms for large data. - Robert Maidstone; Toby Hocking; Guillem Rigaill; Paul Fearnhead (Stat. Comput., 2017)

chipseq. - Toby Hocking (UCI Machine Learning Repository, 2018)

Comparing namedCapture with other R packages for regular expressions. - Toby Dylan Hocking (R J., 2019)

A Graph-Constrained Changepoint Learning Approach for Automatic QRS-Complex Detection. - Atiyeh Fotoohinasab; Toby Hocking; Fatemeh Afghah (ACSSC, 2020)

A Graph-constrained Changepoint Detection Approach for ECG Segmentation. - Atiyeh Fotoohinasab; Toby Hocking; Fatemeh Afghah (EMBC, 2020)

Machine Learning Algorithms for Simultaneous Supervised Detection of Peaks in Multiple Samples andCell Types. - Toby Dylan Hocking; Guillaume Bourque (PSB, 2020)

Linear time dynamic programming for the exact path of optimal models selected from a finite set. - Toby Hocking; Joseph Vargovich (CoRR, 2020)

Constrained Dynamic Programming and Supervised Penalty Learning Algorithms for Peak Detection in Genomic Data. - Toby Dylan Hocking; Guillem Rigaill; Paul Fearnhead; Guillaume Bourque (J. Mach. Learn. Res., 2020)

Fuzz Testing the Compiled Code in R Packages. - Akhila Chowdary Kolla; Alex Groce; Toby Dylan Hocking (ISSRE, 2021)

Increased peak detection accuracy in over-dispersed ChIP-seq data with supervised segmentation models. - Arnaud Liehrmann; Guillem Rigaill; Toby Dylan Hocking (BMC Bioinform., 2021)

A greedy graph search algorithm based on changepoint analysis for automatic QRS complex detection. - Atiyeh Fotoohinasab; Toby Hocking; Fatemeh Afghah (Comput. Biol. Medicine, 2021)

Chatbots language design: the influence of language variation on user experience. - Ana Paula Chaves; Jesse Egbert; Toby Hocking; Eck Doerry; Marco Aurélio Gerosa (CoRR, 2021)

Optimizing ROC Curves with a Sort-Based Surrogate Loss Function for Binary Classification and Changepoint Detection. - Jonathan Hillman; Toby Dylan Hocking (CoRR, 2021)

Wide-to-tall Data Reshaping Using Regular Expressions and the nc Package. - Toby Dylan Hocking (R J., 2021)

Graph Embedding: A Methodological Survey. - Joseph R. Barr; Peter Shaw 001; Faisal N. Abu-Khzam; Tyler Thatcher; Toby Dylan Hocking (TransAI, 2022)

Classifying Imbalanced Data with AUM Loss. - Joseph R. Barr; Toby Dylan Hocking; Garinn Morton; Tyler Thatcher; Peter Shaw 001 (TransAI, 2022)

Interpretable linear models for predicting security vulnerabilities in source code. - Toby Dylan Hocking; Joseph R. Barr; Tyler Thatcher (TransAI, 2022)

Generalized Functional Pruning Optimal Partitioning (GFPOP) for Constrained Changepoint Detection in Genomic Data. - Toby Dylan Hocking; Guillem Rigaill; Paul Fearnhead; Guillaume Bourque (J. Stat. Softw., 2022)

Chatbots Language Design: The Influence of Language Variation on User Experience with Tourist Assistant Chatbots. - Ana Paula Chaves; Jesse Egbert; Toby Hocking; Eck Doerry; Marco Aurélio Gerosa (ACM Trans. Comput. Hum. Interact., 2022)

Linear Time Dynamic Programming for Computing Breakpoints in the Regularization Path of Models Selected From a Finite Set. - Joseph Vargovich; Toby Dylan Hocking (J. Comput. Graph. Stat., 2022)

Survival Regression with Accelerated Failure Time Model in XGBoost. - Avinash Barnwal; Hyunsu Cho; Toby Hocking (J. Comput. Graph. Stat., 2022)

A Log-linear Gradient Descent Algorithm for Unbalanced Binary Classification using the All Pairs Squared Hinge Loss. - Kyle R. Rust; Toby Dylan Hocking (CoRR, 2023)

Optimizing ROC Curves with a Sort-Based Surrogate Loss for Binary Classification and Changepoint Detection. - Jonathan Hillman; Toby Dylan Hocking (J. Mach. Learn. Res., 2023)

gfpop: An R Package for Univariate Graph-Constrained Change-Point Detection. - Vincent Runge; Toby Dylan Hocking; Gaetano Romano; Fatemeh Afghah; Paul Fearnhead; Guillem Rigaill (J. Stat. Softw., 2023)

Predicting Neuromuscular Engagement to Improve Gait Training With a Robotic Ankle Exoskeleton. - Karl Harshe; Jack R. Williams; Toby Dylan Hocking; Zachary F. Lerner (IEEE Robotics Autom. Lett., 2023)

Labeled optimal partitioning. - Toby Dylan Hocking; Anuraag Srivastava (Comput. Stat., 2023)

Deep Learning Approach for Changepoint Detection: Penalty Parameter Optimization. - Tung L. Nguyen; Toby Dylan Hocking (CoRR, 2024)

Efficient line search for optimizing Area Under the ROC Curve in gradient descent. - Jadon Fowler; Toby Dylan Hocking (CoRR, 2024)

SOAK: Same/Other/All K-fold cross-validation for estimating similarity of patterns in data subsets. - Toby Dylan Hocking; Gabrielle Thibault; Cameron Scott Bodine; Paul Nelson Arellano; Alexander F. Shenkin; Olivia Jasmine Lindly (CoRR, 2024)

Finite Sample Complexity Analysis of Binary Segmentation. - Toby Dylan Hocking (CoRR, 2024)

Functional Labeled Optimal Partitioning. - Jacob M. Kaufman; Alyssa J. Stenberg; Toby Dylan Hocking (J. Comput. Graph. Stat., 2024)

Asymptotic benchmarking using the atime package - files and figures for the publication. - Doris Amoakohene; Anirban Chetia; Igor Steinmacher; Toby Hocking (Zenodo, 2025)

Interval Regression: A Comparative Study with Proposed Models. - Tung L. Nguyen; Toby Dylan Hocking (CoRR, 2025)

Learning Penalty for Optimal Partitioning via Automatic Feature Extraction. - Tung L. Nguyen; Toby Hocking (CoRR, 2025)

Penalty Learning for Optimal Partitioning using Multilayer Perceptron. - Tung L. Nguyen; Toby Dylan Hocking (Stat. Comput., 2025)

Cross-validation for training and testing co-occurrence network inference algorithms. - Daniel Agyapong; Jeffrey Ryan Propster; Jane Marks; Toby Dylan Hocking (BMC Bioinform., 2025)