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- Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopa
- 2016 IEEE Power and Energy Society Generalâ€¦
- 2016

Summary form only given. This paper studies the general problem of operating energy storage under uncertainty. Two fundamental sources of uncertainty are considered, namely the uncertainty in theâ€¦ (More)

- Junjie Qin, Yinlam Chow, Jiyan Yang, Ram Rajagopal
- IEEE Transactions on Smart Grid
- 2016

The integration of intermittent and stochastic renewable energy resources requires increased flexibility in the operation of the electric grid. Storage, broadly speaking, provides the flexibility ofâ€¦ (More)

- Jiyan Yang, Yinlam Chow, Christopher RÃ©, Michael W. Mahoney
- SODA
- 2016

In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and data analysis. SGDâ€¦ (More)

- Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone
- Journal of Machine Learning Research
- 2017

In many sequential decision-making problems one is interested in minimizing an expected cumulative cost while taking into account risk, i.e., increased awareness of events of small probability andâ€¦ (More)

- Yinlam Chow, Aviv Tamar, Shie Mannor, Marco Pavone
- NIPS
- 2015

In this paper we address the problem of decision making within a Markov decision process (MDP) framework where risk and modeling errors are taken into account. Our approach is to minimize aâ€¦ (More)

- Mohammad Ghavamzadeh, Marek Petrik, Yinlam Chow
- NIPS
- 2016

An important problem in sequential decision-making under uncertainty is to use limited data to compute a safe policy, which is guaranteed to outperform a given baseline strategy. In this paper, weâ€¦ (More)

- Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh, Shie Mannor
- NIPS
- 2015

Risk-sensitive optimization considers problems in which the objective involves a risk measure of the random cost, in contrast to the typical expected cost objective. Such problems are important whenâ€¦ (More)

In many real-world reinforcement learning (RL) problems, besides optimizing the main objective function, an agent must concurrently avoid violating a number of constraints. In particular, besidesâ€¦ (More)

- Stefano Carpin, Yinlam Chow, Marco Pavone
- 2016 IEEE International Conference on Roboticsâ€¦
- 2016

In this paper we present an algorithm to compute risk averse policies in Markov Decision Processes (MDP) when the total cost criterion is used together with the average value at risk (AVaR) metric.â€¦ (More)

- Yinlam Chow, Mohammad Ghavamzadeh
- NIPS
- 2014

In many sequential decision-making problems we may want to manage risk by minimizing some measure of variability in costs in addition to minimizing a standard criterion. Conditional value-at-riskâ€¦ (More)