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ORCIDTucker R. Balch
Tucker Balch – Tucker Hybinette Balch
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- affiliation: Georgia Institute of Technology, Atlanta, USA
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2020 – today
- 2023
[j36]Sahar Mazloom, Benjamin E. Diamond, Antigoni Polychroniadou, Tucker Balch:
An Efficient Data-Independent Priority Queue and its Application to Dark Pools. Proc. Priv. Enhancing Technol. 2023(2): 5-22 (2023)- [i34]Andrea Coletta, Svitlana Vyetrenko, Tucker Balch:
K-SHAP: Policy Clustering Algorithm for Anonymous State-Action Pairs. CoRR abs/2302.11996 (2023) - [i33]Zhen Zeng, Rachneet Kaur, Suchetha Siddagangappa, Saba Rahimi, Tucker Balch, Manuela Veloso:
Financial Time Series Forecasting using CNN and Transformer. CoRR abs/2304.04912 (2023) - [i32]Antigoni Polychroniadou, Gilad Asharov, Benjamin E. Diamond, Tucker Balch, Hans Buehler, Richard Hua, Suwen Gu, Greg Gimler, Manuela Veloso:
Prime Match: A Privacy-Preserving Inventory Matching System. IACR Cryptol. ePrint Arch. 2023: 400 (2023) - 2022
- [c93]David Byrd, Vaikkunth Mugunthan, Antigoni Polychroniadou, Tucker Balch:
Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy. ICAIF 2022: 114-122 - [c92]Sahar Mazloom, Antigoni Polychroniadou, Tucker Balch:
Addressing Extreme Market Responses Using Secure Aggregation. ICAIF 2022: 192-198 - [c91]Kshama Dwarakanath, Svitlana Vyetrenko, Tucker Balch:
Equitable Marketplace Mechanism Design. ICAIF 2022: 232-239 - [c90]Andrea Coletta, Aymeric Moulin, Svitlana Vyetrenko, Tucker Balch:
Learning to simulate realistic limit order book markets from data as a World Agent. ICAIF 2022: 428-436 - [c89]Yuanlu Bai, Henry Lam, Tucker Balch, Svitlana Vyetrenko:
Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization. ICAIF 2022: 437-445 - [c88]Kshama Dwarakanath, Danial Dervovic, Peyman Tavallali, Svitlana Vyetrenko, Tucker Balch:
Optimal Stopping with Gaussian Processes. ICAIF 2022: 497-505 - [c87]Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba, Vamsi K. Potluru, Tucker Balch, Sameena Shah, Manuela Veloso:
Online Learning for Mixture of Multivariate Hawkes Processes. ICAIF 2022: 506-513 - [e5]Daniele Magazzeni, Senthil Kumar, Rahul Savani, Renyuan Xu, Carmine Ventre, Blanka Horvath, Ruimeng Hu, Tucker Balch, Francesca Toni:
3rd ACM International Conference on AI in Finance, ICAIF 2022, New York, NY, USA, November 2-4, 2022. ACM 2022, ISBN 978-1-4503-9376-8 [contents] - [i31]Selim Amrouni, Aymeric Moulin, Tucker Balch:
CTMSTOU driven markets: simulated environment for regime-awareness in trading policies. CoRR abs/2202.00941 (2022) - [i30]David Byrd, Vaikkunth Mugunthan, Antigoni Polychroniadou, Tucker Hybinette Balch:
Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy. CoRR abs/2202.09897 (2022) - [i29]Mohsen Ghassemi, Eleonora Kreacic, Niccolò Dalmasso, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Differentially Private Learning of Hawkes Processes. CoRR abs/2207.13741 (2022) - [i28]Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba, Vamsi K. Potluru, Sameena Shah, Tucker Balch, Manuela Veloso:
Online Learning for Mixture of Multivariate Hawkes Processes. CoRR abs/2208.07961 (2022) - [i27]Kshama Dwarakanath, Danial Dervovic, Peyman Tavallali, Svitlana S. Vyetrenko, Tucker Balch:
Optimal Stopping with Gaussian Processes. CoRR abs/2209.14738 (2022) - [i26]Kshama Dwarakanath, Svitlana S. Vyetrenko, Tucker Balch:
Equitable Marketplace Mechanism Design. CoRR abs/2209.15418 (2022) - [i25]Nelson Vadori, Leo Ardon, Sumitra Ganesh, Thomas Spooner, Selim Amrouni, Jared Vann, Mengda Xu, Zeyu Zheng, Tucker Balch, Manuela Veloso:
Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations. CoRR abs/2210.07184 (2022) - [i24]Andrea Coletta, Aymeric Moulin, Svitlana Vyetrenko, Tucker Balch:
Learning to simulate realistic limit order book markets from data as a World Agent. CoRR abs/2210.09897 (2022) - [i23]Renbo Zhao, Niccolò Dalmasso, Mohsen Ghassemi, Vamsi K. Potluru, Tucker Balch, Manuela Veloso:
Fast Learning of Multidimensional Hawkes Processes via Frank-Wolfe. CoRR abs/2212.06081 (2022) - [i22]Yue Guo, Antigoni Polychroniadou, Elaine Shi, David Byrd, Tucker Balch:
MicroFedML: Privacy Preserving Federated Learning for Small Weights. IACR Cryptol. ePrint Arch. 2022: 714 (2022) - 2021
- [c86]Kshama Dwarakanath, Svitlana S. Vyetrenko, Tucker Balch:
Profit equitably: an investigation of market maker's impact on equitable outcomes. ICAIF 2021: 4:1-4:8 - [c85]Mahmoud Mahfouz, Tucker Balch, Manuela Veloso, Danilo P. Mandic:
Learning to classify and imitate trading agents in continuous double auction markets. ICAIF 2021: 21:1-21:8 - [c84]Srijan Sood, Zhen Zeng, Naftali Cohen, Tucker Balch, Manuela Veloso:
Visual time series forecasting: an image-driven approach. ICAIF 2021: 22:1-22:9 - [c83]Selim Amrouni, Aymeric Moulin, Jared Vann, Svitlana Vyetrenko, Tucker Balch, Manuela Veloso:
ABIDES-gym: gym environments for multi-agent discrete event simulation and application to financial markets. ICAIF 2021: 30:1-30:9 - [c82]Gilad Asharov, Tucker Balch, Antigoni Polychroniadou:
Privacy-preserving portfolio pricing. ICAIF 2021: 35:1-35:8 - [c81]Zhen Zeng, Tucker Balch, Manuela Veloso:
Deep video prediction for time series forecasting. ICAIF 2021: 39:1-39:7 - [c80]Andrea Coletta, Matteo Prata, Michele Conti, Emanuele Mercanti, Novella Bartolini, Aymeric Moulin, Svitlana Vyetrenko, Tucker Balch:
Towards realistic market simulations: a generative adversarial networks approach. ICAIF 2021: 46:1-46:9 - [c79]Megan Shearer, David Byrd, Tucker Hybinette Balch, Michael P. Wellman:
Stability effects of arbitrage in exchange traded funds: an agent-based model. ICAIF 2021: 49:1-49:9 - [i21]Zhen Zeng, Tucker Balch, Manuela Veloso:
Deep Video Prediction for Time Series Forecasting. CoRR abs/2102.12061 (2021) - [i20]Yuanlu Bai, Tucker Balch, Haoxian Chen, Danial Dervovic, Henry Lam, Svitlana Vyetrenko:
Calibrating Over-Parametrized Simulation Models: A Framework via Eligibility Set. CoRR abs/2105.12893 (2021) - [i19]Naftali Cohen, Srijan Sood, Zhen Zeng, Tucker Balch, Manuela Veloso:
Visual Time Series Forecasting: An Image-driven Approach. CoRR abs/2107.01273 (2021) - [i18]Victor Storchan, Svitlana Vyetrenko, Tucker Balch:
Learning who is in the market from time series: market participant discovery through adversarial calibration of multi-agent simulators. CoRR abs/2108.00664 (2021) - [i17]Mahmoud Mahfouz, Tucker Balch, Manuela Veloso, Danilo P. Mandic:
Learning to Classify and Imitate Trading Agents in Continuous Double Auction Markets. CoRR abs/2110.01325 (2021) - [i16]Andrea Coletta, Matteo Prata, Michele Conti, Emanuele Mercanti, Novella Bartolini, Aymeric Moulin, Svitlana Vyetrenko, Tucker Balch:
Towards Realistic Market Simulations: a Generative Adversarial Networks Approach. CoRR abs/2110.13287 (2021) - [i15]Selim Amrouni, Aymeric Moulin, Jared Vann, Svitlana Vyetrenko, Tucker Balch, Manuela Veloso:
ABIDES-Gym: Gym Environments for Multi-Agent Discrete Event Simulation and Application to Financial Markets. CoRR abs/2110.14771 (2021) - [i14]Kshama Dwarakanath, Svitlana S. Vyetrenko, Tucker Balch:
Profit equitably: An investigation of market maker's impact on equitable outcomes. CoRR abs/2111.00094 (2021) - [i13]Yuanlu Bai, Henry Lam, Svitlana Vyetrenko, Tucker Balch:
Efficient Calibration of Multi-Agent Market Simulators from Time Series with Bayesian Optimization. CoRR abs/2112.03874 (2021) - 2020
- [c78]Gilad Asharov, Tucker Hybinette Balch, Antigoni Polychroniadou, Manuela Veloso:
Privacy-Preserving Dark Pools. AAMAS 2020: 1747-1749 - [c77]Svitlana Vyetrenko, David Byrd, Nick Petosa, Mahmoud Mahfouz, Danial Dervovic, Manuela Veloso, Tucker Balch:
Get real: realism metrics for robust limit order book market simulations. ICAIF 2020: 2:1-2:8 - [c76]Tucker Balch, Benjamin E. Diamond, Antigoni Polychroniadou:
SecretMatch: inventory matching from fully homomorphic encryption. ICAIF 2020: 15:1-15:7 - [c75]Joshua Lockhart, Samuel Assefa, Ayham Alajdad, Andrew Alexander, Tucker Balch, Manuela Veloso:
SURF: improving classifiers in production by learning from busy and noisy end users. ICAIF 2020: 37:1-37:8 - [c74]Naftali Cohen, Tucker Balch, Manuela Veloso:
Trading via image classification. ICAIF 2020: 53:1-53:6 - [c73]David Byrd, Maria Hybinette, Tucker Hybinette Balch:
ABIDES: Towards High-Fidelity Multi-Agent Market Simulation. SIGSIM-PADS 2020: 11-22 - [e4]Tucker Balch:
ICAIF '20: The First ACM International Conference on AI in Finance, New York, NY, USA, October 15-16, 2020. ACM 2020, ISBN 978-1-4503-7584-9 [contents] - [i12]Micah Goldblum, Avi Schwarzschild, Naftali Cohen, Tucker Balch, Ankit B. Patel, Tom Goldstein:
Adversarial Attacks on Machine Learning Systems for High-Frequency Trading. CoRR abs/2002.09565 (2020) - [i11]Joshua Lockhart, Samuel Assefa, Tucker Balch, Manuela Veloso:
Some people aren't worth listening to: periodically retraining classifiers with feedback from a team of end users. CoRR abs/2004.13152 (2020) - [i10]Joshua Lockhart, Samuel Assefa, Ayham Alajdad, Andrew Alexander, Tucker Balch, Manuela Veloso:
SURF: Improving classifiers in production by learning from busy and noisy end users. CoRR abs/2010.05852 (2020) - [i9]Naftali Cohen, Srijan Sood, Zhen Zeng, Tucker Balch, Manuela Veloso:
Visual Forecasting of Time Series with Image-to-Image Regression. CoRR abs/2011.09052 (2020)
2010 – 2019
- 2019
- [i8]David Byrd, Maria Hybinette, Tucker Hybinette Balch:
ABIDES: Towards High-Fidelity Market Simulation for AI Research. CoRR abs/1904.12066 (2019) - [i7]Tucker Hybinette Balch, Mahmoud Mahfouz, Joshua Lockhart, Maria Hybinette, David Byrd:
How to Evaluate Trading Strategies: Single Agent Market Replay or Multiple Agent Interactive Simulation? CoRR abs/1906.12010 (2019) - [i6]Naftali Cohen, Tucker Balch, Manuela Veloso:
The Effect of Visual Design in Image Classification. CoRR abs/1907.09567 (2019) - [i5]Naftali Cohen, Tucker Balch, Manuela Veloso:
Trading via Image Classification. CoRR abs/1907.10046 (2019) - [i4]David Byrd, Tucker Hybinette Balch:
Intra-day Equity Price Prediction using Deep Learning as a Measure of Market Efficiency. CoRR abs/1908.08168 (2019) - [i3]Nick Petosa, Tucker Balch:
Multiplayer AlphaZero. CoRR abs/1910.13012 (2019) - [i2]Svitlana Vyetrenko, David Byrd, Nick Petosa, Mahmoud Mahfouz, Danial Dervovic, Manuela Veloso, Tucker Hybinette Balch:
Get Real: Realism Metrics for Robust Limit Order Book Market Simulations. CoRR abs/1912.04941 (2019) - 2018
- [c72]Brian Hrolenok, Tucker Balch, David Byrd, Rebecca Roberts, Chanho Kim, James M. Rehg
, Scott Gilliland, Kim Wallen:
Use of position tracking to infer social structure in rhesus macaques. ACI 2018: 15:1-15:5 - 2017
- [c71]Brian Hrolenok, Byron Boots, Tucker Hybinette Balch:
Sampling Beats Fixed Estimate Predictors for Cloning Stochastic Behavior in Multiagent Systems. AAAI 2017: 2022-2028 - [c70]Jianling Wang, Vivek George, Tucker Balch, Maria Hybinette:
Stockyard: A discrete event-based stock market exchange simulator. WSC 2017: 1193-1203 - 2016
- [j35]Alexander Moreno, Tucker Balch:
Improving financial computation speed with full and subproblem memoization. Concurr. Comput. Pract. Exp. 28(3): 905-915 (2016) - 2014
- [j34]Michael Misha Novitzky, Charles Pippin, Thomas R. Collins, Tucker R. Balch, Michael E. West:
AUV behavior recognition using behavior histograms, HMMs, and CRFs. Robotica 32(2): 291-304 (2014) - [c69]Brian Hrolenok, Hanuma Teja Maddali, Michael Misha Novitzky, Tucker Balch:
Inferring Social Structure of Animal Groups from Tracking Data. ALIFE 2014: 336-343 - [c68]Brian Hrolenok, Tucker R. Balch:
Assessing learned models of fish schooling behavior. AAMAS 2014: 1435-1436 - [c67]Alexander Moreno, Tucker Balch:
Speeding up large-scale financial recomputation with memoization. WHPCF@SC 2014: 17-22 - [c66]Terrance Medina, Maria Hybinette, Tucker R. Balch:
Behavior-based code generation for robots and autonomous agents. SimuTools 2014: 172-177 - [i1]Hanuma Teja Maddali, Michael Misha Novitzky, Brian Hrolenok, Daniel Walker, Tucker R. Balch, Kim Wallen:
Inferring Social Structure and Dominance Relationships Between Rhesus macaques using RFID Tracking Data. CoRR abs/1407.0330 (2014) - 2013
- [c65]Brian Hrolenok, Tucker R. Balch:
Learning Schooling Behavior from Observation. ECAL 2013: 686-691 - 2012
- [j33]Adam Feldman, Maria Hybinette, Tucker R. Balch:
The multi-iterative closest point tracker: An online algorithm for tracking multiple interacting targets. J. Field Robotics 29(2): 258-276 (2012) - [c64]Michael Misha Novitzky, Charles Pippin, Thomas R. Collins, Tucker R. Balch, Michael E. West:
Conditional Random Fields for Behavior Recognition of Autonomous Underwater Vehicles. DARS 2012: 409-421 - [c63]Yu-Ting Yang, Andrew Quitmeyer, Brian Hrolenok, Harry Shang, Dinh Bao Nguyen, Tucker R. Balch, Terrance Medina, Cole Sherer, Maria Hybinette:
Ant Hunt: Towards a Validated Model of Live Ant Hunting Behavior. FLAIRS 2012 - [c62]Pipei Huang, Rahul Sawhney, Daniel Walker, Kim Wallen, Aaron F. Bobick, Shiyin Qin, Tucker R. Balch:
Learning a projective mapping to locate animals in video using RFID. IROS 2012: 3830-3836 - [c61]Michael Misha Novitzky, Charles Pippin, Thomas R. Collins, Tucker R. Balch, Michael E. West:
Bio-inspired multi-robot communication through behavior recognition. ROBIO 2012: 771-776 - 2011
- [j32]Rick Cavallaro, Maria Hybinette, Marvin White, Tucker R. Balch:
Augmenting Live Broadcast Sports with 3D Tracking Information. IEEE Multim. 18(4): 38-47 (2011) - [j31]Sanem Sariel Talay, Tucker R. Balch, Nadia Erdogan:
A Generic Framework for Distributed Multirobot Cooperation. J. Intell. Robotic Syst. 63(2): 323-358 (2011) - 2010
- [c60]Matthew Powers, Tucker R. Balch:
Incremental adaptive integration of layers of a hybrid control architecture. IROS 2010: 2012-2017
2000 – 2009
- 2009
- [j30]Richard Roberts, Charles Pippin, Tucker R. Balch:
Learning outdoor mobile robot behaviors by example. J. Field Robotics 26(2): 176-195 (2009) - [j29]Xu Chu Ding, Matthew Powers, Magnus Egerstedt, Shih-Yih Young, Tucker R. Balch:
Executive decision support. IEEE Robotics Autom. Mag. 16(2): 73-81 (2009) - [c59]Jinhan Lee, Roozbeh Mottaghi, Charles Pippin, Tucker R. Balch:
Graph-based planning using local information for unknown outdoor environments. ICRA 2009: 1455-1460 - [c58]Matthew Powers, Tucker R. Balch:
A learning approach to integration of layers of a hybrid control architecture. IROS 2009: 893-898 - [c57]Jay Summet, Deepak Kumar, Keith J. O'Hara, Daniel Walker, Lijun Ni, Douglas S. Blank, Tucker R. Balch:
Personalizing CS1 with robots. SIGCSE 2009: 433-437 - 2008
- [j28]Sang Min Oh, James M. Rehg, Tucker R. Balch, Frank Dellaert:
Learning and Inferring Motion Patterns using Parametric Segmental Switching Linear Dynamic Systems. Int. J. Comput. Vis. 77(1-3): 103-124 (2008) - [j27]Tucker R. Balch, Jay Summet, Douglas S. Blank, Deepak Kumar, Mark Guzdial, Keith J. O'Hara, Daniel Walker, Monica Sweat, Gaurav Gupta, Stewart Tansley, Jared Jackson, Mansi Gupta, Marwa Nur Muhammad, Shikha Prashad, Natasha Eilbert, Ashley Gavin:
Designing Personal Robots for Education: Hardware, Software, and Curriculum. IEEE Pervasive Comput. 7(2): 5-9 (2008) - [j26]Sanem Sariel, Tucker R. Balch, Nadia Erdogan:
Naval Mine Countermeasure Missions. IEEE Robotics Autom. Mag. 15(1): 45-52 (2008) - [j25]Keith J. O'Hara, Daniel B. Walker, Tucker R. Balch:
Physical Path Planning Using a Pervasive Embedded Network. IEEE Trans. Robotics 24(3): 741-746 (2008) - [c56]Deepak Kumar, Douglas S. Blank, Tucker R. Balch, Keith J. O'Hara, Mark Guzdial, Stewart Tansley:
Engaging Computing Students with AI and Robotics. AAAI Spring Symposium: Using AI to Motivate Greater Participation in Computer Science 2008: 55-60 - [c55]Richard Roberts, Hai Nguyen, Niyant Krishnamurthi, Tucker R. Balch:
Memory-based learning for visual odometry. ICRA 2008: 47-52 - [c54]Jinhan Lee, Charles Pippin, Tucker R. Balch:
Cost based planning with RRT in outdoor environments. IROS 2008: 684-689 - 2007
- [j24]David Wooden, Matthew Powers, Magnus Egerstedt, Henrik I. Christensen, Tucker R. Balch:
A Modular, Hybrid System Architecture for Autonomous, Urban Driving. J. Aerosp. Comput. Inf. Commun. 4(12): 1047-1058 (2007) - [c53]Adam Feldman, Summer Adams, Maria Hybinette, Tucker R. Balch:
A Tracker for Multiple Dynamic Targets Using Multiple Sensors. ICRA 2007: 3140-3141 - [c52]Sanem Sariel, Tucker R. Balch, Nadia Erdogan:
Incremental multi-robot task selection for resource constrained and interrelated tasks. IROS 2007: 2314-2319 - [c51]David Wooden, Matthew Powers, Douglas C. MacKenzie, Tucker R. Balch, Magnus Egerstedt:
Control-driven mapping and planning. IROS 2007: 3056-3061 - 2006
- [j23]Jie Sun, Tejas R. Mehta, David Wooden, Matthew Powers, James M. Rehg, Tucker R. Balch, Magnus Egerstedt:
Learning from examples in unstructured, outdoor environments. J. Field Robotics 23(11-12): 1019-1036 (2006) - [j22]Zia Khan, Tucker R. Balch, Frank Dellaert:
MCMC Data Association and Sparse Factorization Updating for Real Time Multitarget Tracking with Merged and Multiple Measurements. IEEE Trans. Pattern Anal. Mach. Intell. 28(12): 1960-1972 (2006) - [j21]Tucker R. Balch, Frank Dellaert, Adam Feldman, Andrew Guillory, Charles Lee Isbell Jr., Zia Khan, Stephen C. Pratt, Andrew N. Stein, Hank Wilde:
How Multirobot Systems Research will Accelerate our Understanding of Social Animal Behavior. Proc. IEEE 94(7): 1445-1463 (2006) - [c50]Andrew Guillory, Hai Nguyen, Tucker R. Balch, Charles Lee Isbell Jr.:
Learning executable agent behaviors from observation. AAMAS 2006: 795-797 - [c49]Sanem Sariel, Tucker Balch:
A Distributed Multi-robot Cooperation Framework for Real Time Task Achievement. DARS 2006: 187-196 - [c48]Sanem Sariel, Tucker Balch, Jason R. Stack:
Empirical Evaluation of Auction-Based Coordination of AUVs in a Realistic Simulated Mine Countermeasure Task. DARS 2006: 197-206 - [c47]Sanem Sariel, Tucker R. Balch:
Efficient Bids on Task Allocation for Multi-Robot Exploration. FLAIRS 2006: 116-121 - [c46]Sanem Sariel, Tucker R. Balch, Nadia Erdogan:
Robust multi-robot cooperation through dynamic task allocation and precaution routines. ICINCO-RA 2006: 196-201 - [c45]Keith J. O'Hara, Victor Bigio, Shaun Whitt, Daniel Walker, Tucker R. Balch:
Evaluation of a Large Scale Pervasive Embedded Network for Robot Path Planning. ICRA 2006: 2072-2077 - [c44]Keith J. O'Hara, Ripal Nathuji, Himanshu Raj, Karsten Schwan, Tucker R. Balch:
AutoPower: Toward Energy-aware Software Systems for Distributed Mobile Robots. ICRA 2006: 2757-2762 - [c43]Himanshu Raj, Balasubramanian Seshasayee, Keith J. O'Hara, Ripal Nathuji, Karsten Schwan, Tucker R. Balch:
Spirits: Using Virtualization and Pervasiveness to Manage Mobile Robot Software Systems. SelfMan 2006: 116-129 - [e3]Tamio Arai, Rolf Pfeifer, Tucker R. Balch, Hiroshi Yokoi:
Intelligent Autonomous Systems 9 - IAS-9, Proceedings of the 9th International Conference on Intelligent Autonomous Systems, University of Tokyo, Tokyo, Japan, March 7-9, 2006. IOS Press 2006, ISBN 1-58603-595-9 [contents] - 2005
- [j20]Zia Khan, Tucker R. Balch, Frank Dellaert:
MCMC-Based Particle Filtering for Tracking a Variable Number of Interacting Targets. IEEE Trans. Pattern Anal. Mach. Intell. 27(11): 1805-1918 (2005) - [j19]Ashley W. Stroupe, Tucker R. Balch:
Value-based action selection for observation with robot teams using probabilistic techniques. Robotics Auton. Syst. 50(2-3): 85-97 (2005) - [c42]Sang Min Oh, James M. Rehg, Tucker R. Balch, Frank Dellaert:
Data-Driven MCMC for Learning and Inference in Switching Linear Dynamic Systems. AAAI 2005: 944-949 - [c41]Zia Khan, Tucker R. Balch, Frank Dellaert:
Multitarget Tracking with Split and Merged Measurements. CVPR (1) 2005: 605-610 - [c40]Sang Min Oh, James M. Rehg, Tucker R. Balch, Frank Dellaert:
Learning and Inference in Parametric Switching Linear Dynamical Systems. ICCV 2005: 1161-1168 - [c39]Keith J. O'Hara, Victor Bigio, Eric R. Dodson, Arya Irani, Daniel Walker, Tucker R. Balch:
Physical Path Planning Using the GNATs. ICRA 2005: 709-714 - [c38]Magnus Egerstedt, Tucker R. Balch, Frank Dellaert, Florent Delmotte, Zia Khan:
What Are the Ants Doing? Vision-Based Tracking and Reconstruction of Control Programs. ICRA 2005: 4182-4187 - 2004
- [j18]Carl Anderson, Tucker R. Balch:
Special Issue on Mathematics and Algorithms of Social Interactions. Adapt. Behav. 12(3-4): 145-146 (2004) - [j17]Patrick Ulam, Tucker R. Balch:
Using Optimal Foraging Models to Evaluate Learned Robotic Foraging Behavior. Adapt. Behav. 12(3-4): 213-222 (2004) - [j16]Adam Feldman, Tucker R. Balch:
Representing Honey Bee Behavior for Recognition Using Human Trainable Models. Adapt. Behav. 12(3-4): 241-250 (2004) - [c37]Keith J. O'Hara, Tucker R. Balch:
Distributed Path Planning for Robots in Dynamic Environments Using a Pervasive Embedded Network. AAMAS 2004: 1538-1539 - [c36]Zia Khan, Tucker R. Balch, Frank Dellaert:
A Rao-Blackwellized Particle Filter for EigenTracking. CVPR (2) 2004: 980-986 - [c35]Keith J. O'Hara, Tucker R. Balch:
Pervasive Sensor-less Networks for Cooperative Multi-robot Tasks. DARS 2004: 305-314 - [c34]