Books

• J. Choi and G. Friedland, Eds., Multimodal Location Estimation of Videos and Images, Springer, 2014.
• G. Friedland and R. Jain, Introduction to Multimedia Computing, Cambridge University Press, 2014.

Articles in journals or magazines

• B. Thomee, D. Shamma, G. Friedland, B. Elizalde, K. Ni, D. Poland, and D. Borth, "YFCC100M: The New Data in Multimedia Research," Communications of the ACM (CACM), vol. 59, no. 2, pp. 64-73, Feb. 2016.
• E. Gonina, G. Friedland, E. Battenberg, P. Koanantakool, M. Driscoll, E. Georganas, and K. Keutzer, "Scalable Multimedia Content Analysis on Parallel Platforms Using Python," ACM Trans. Multimedia Comput. Commun. Appl., vol. 10, no. 2, pp. 18:1--18:22, Feb. 2014.

Masters Reports

• H. Guo, G. Friedland, and G. K. Anumanchipalli, "Enhancing GAN-based Vocoders with Contrastive Learning," EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2023-183, May 2023.
• A. Hiremath, "Multimodal Contrastive Learning for Unsupervised Video Representation Learning," A. Zakhor and G. Friedland, Eds., EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2022-206, Aug. 2022.
• N. Hyder and G. Friedland, "Learning Rate Estimation for Stochastic Gradient Descent," EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2022-155, May 2022.
• L. Song, Z. Zhang, A. Panda, Y. Yang, M. Mahoney, J. Gonzalez, and P. Prateek Mittal, "Neurotoxin: Durable Backdoors in Federated Learning," K. Ramchandran and G. Friedland, Eds., EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2022-89, May 2022.
• D. Nahm, "On the Robustness of Learned Task Weights in Cross-modal Retrieval," G. Friedland and K. Ramchandran, Eds., EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2020-86, May 2020.