List of Publications

You can find my updated list of publications within my scholar page.

  • S. V., A. K., R. B., N. L., Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees, DP4ML workshop ICML’23. [pdf]
  • B. Z., Y. S., R. B., Fast Online Node Labeling for Very Large Graphs, ICML’23. [pdf][code]
  • J. L., S. V., R. B., M. S., N. L., Target-based Surrogates for Stochastic Optimization, ICML’23. [pdf] [code]
  • B. D., S. V., R. B., "Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent", ICML, 2022. [pdf] [code]
  • A. J., S. V., R. B., C. S., D. P., "Towards Painless Policy Optimization for Constrained MDPs", UAI, 2022. [pdf] [code]
  • B. D., S. V., R. B., M. S., S. L. J., "SVRG meets AdaGrad: Painless Variance Reduction", ECML, 2022. [pdf] [code]
  • L. L., Y. Z., Z. Y., R. B. , Z. W., "Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport", ICML, 2021. [pdf]
  • R. L., B. R.,et al., "An Analysis of Causal Models Adaptation Speed", AISTAT 2021. [pdf][code]
  • V. S., B. R.,et al., "To Each Optimizer a Norm, To Each Norm its Generalization", NeurIPS optimization workshop 2020. [pdf]
  • R.B., S. L. J., Geometry-Aware Universal Mirror-Prox, Arxiv, 2020. [pdf]
  • A. D, A. D. B. R.,et al.,, "Reducing the variance in online optimization by transporting past gradients", NeurIPS 2019. [pdf]
  • D. A., B. E., B. R., "Manifold Preserving Adversarial Learning", ArXiv, 2019. [pdf]
  • B.R. , et. al., "MASAGA: A Stochastic Algorithm for Manifold Optimization", ECML 2018. [pdf],[code]
  • L.I.,B.R. , et. al., "Domain Adaptation with Deep Metric Learning", ICML DAVU workshop, 2018. [pdf],[code]
  • L. N. ,B.R. , et. al., "Online variance-reducing optimization", ICLR 2018, Workshop Track. [pdf]
  • Z.Z., B.R. . , et. al., "A Generic Top-N Recommendation Framework For Trading-off Accuracy, Novelty, and Coverage", ICDE 2018. [pdf]
  • K. M., B.R., , et. al., "Faster Stochastic Variational Inference using Proximal-Gradient Methods with General Divergence Functions.", UAI 2016. [pdf][Poster]
  • B. R. , et. al., "Stop Wasting My Gradients: Practical SVRG.", NIPS 2015. [pdf][Poster][Slides][code]
  • S. M., B. R. , et. al., "Non-Uniform Stochastic Average Gradient Method for Training Conditional Random Fields", AISTATS 2015. [pdf][Poster][Slides][code]
  • W. E., B. R. , "Denormalization Middleware for Database-as-a-Service", SOCA 2013.
  • B. R. , et. al., "Process Pattern for Web Engineering", COMPSAC 2010.


  1. "Convergence Rate for EM algorithm" in ISMP and WCOM, 2018. [Slide]
  2. "Stop Wasting My Gradients: Practical SVRG" in ICCOP and WCOM, 2015. [Slide]