Search Results - "Gottesman, Omer"

iCVS—Inferring Cardio-Vascular hidden States from physiological signals available at the bedside by Ravid Tannenbaum, Neta, Gottesman, Omer, Assadi, Azadeh, Mazwi, Mjaye, Shalit, Uri, Eytan, Danny

“…Intensive care medicine is complex and resource-demanding. A critical and common challenge lies in inferring the underlying physiological state of a patient…”
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A state variable for crumpled thin sheets by Gottesman, Omer, Andrejevic, Jovana, Rycroft, Chris H., Rubinstein, Shmuel M.

“…Despite the apparent ease with which sheets of paper are crumpled and tossed away, crumpling dynamics are often considered a paradigm of complexity. This…”
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Improving counterfactual reasoning with kernelised dynamic mixing models by Parbhoo, Sonali, Gottesman, Omer, Ross, Andrew Slavin, Komorowski, Matthieu, Faisal, Aldo, Bon, Isabella, Roth, Volker, Doshi-Velez, Finale

“…Simulation-based approaches to disease progression allow us to make counterfactual predictions about the effects of an untried series of treatment choices…”
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Guidelines for reinforcement learning in healthcare by Gottesman, Omer, Johansson, Fredrik, Komorowski, Matthieu, Faisal, Aldo, Sontag, David, Doshi-Velez, Finale, Celi, Leo Anthony

“…In this Comment, we provide guidelines for reinforcement learning for decisions about patient treatment that we hope will accelerate the rate at which…”
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Nonmonotonic Aging and Memory Retention in Disordered Mechanical Systems by Lahini, Yoav, Gottesman, Omer, Amir, Ariel, Rubinstein, Shmuel M

“…We observe nonmonotonic aging and memory effects, two hallmarks of glassy dynamics, in two disordered mechanical systems: crumpled thin sheets and elastic…”
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Furrows in the wake of propagating d-cones by Gottesman, Omer, Efrati, Efi, Rubinstein, Shmuel M.

“…A crumpled sheet of paper displays an intricate pattern of creases and point-like singular structures, termed d-cones. It is typically assumed that elongated…”
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Localized patterns in crushed conical shells by Gottesman, Omer, Vouga, Etienne, Rubinstein, Shmuel M., Mahadevan, L.

“…We use experiments and numerical simulations to study the rapid buckling of thin-walled cones as they impact a solid surface at high velocities. The buildup of…”
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Off-Policy Evaluation of Reinforcement Learning in Healthcare by Gottesman, Omer

“…Reinforcement learning is a method for learning optimal strategies for tasks which require making sequences of decisions. The ability to make decisions in a…”
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Improving Sepsis Treatment Strategies by Combining Deep and Kernel-Based Reinforcement Learning by Peng, Xuefeng, Ding, Yi, Wihl, David, Gottesman, Omer, Komorowski, Matthieu, Lehman, Li-Wei H, Ross, Andrew, Faisal, Aldo, Doshi-Velez, Finale

“…Sepsis is the leading cause of mortality in the ICU. It is challenging to manage because individual patients respond differently to treatment. Thus, tailoring…”
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Multiple extinction routes in stochastic population models by Gottesman, Omer, Meerson, Baruch

“…Isolated populations ultimately go extinct because of the intrinsic noise of elementary processes. In multipopulation systems extinction of a population may…”
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On the Geometry of Reinforcement Learning in Continuous State and Action Spaces by Tiwari, Saket, Gottesman, Omer, Konidaris, George

“…Advances in reinforcement learning have led to its successful application in complex tasks with continuous state and action spaces. Despite these advances in…”
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TD Convergence: An Optimization Perspective by Asadi, Kavosh, Sabach, Shoham, Liu, Yao, Gottesman, Omer, Fakoor, Rasool

“…We study the convergence behavior of the celebrated temporal-difference (TD) learning algorithm. By looking at the algorithm through the lens of optimization,…”
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Decision-Focused Model-based Reinforcement Learning for Reward Transfer by Sharma, Abhishek, Parbhoo, Sonali, Gottesman, Omer, Doshi-Velez, Finale

“…Decision-focused (DF) model-based reinforcement learning has recently been introduced as a powerful algorithm that can focus on learning the MDP dynamics that…”
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A Bayesian Approach to Learning Bandit Structure in Markov Decision Processes by Zhang, Kelly W, Gottesman, Omer, Doshi-Velez, Finale

“…In the reinforcement learning literature, there are many algorithms developed for either Contextual Bandit (CB) or Markov Decision Processes (MDP)…”
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Learning Markov State Abstractions for Deep Reinforcement Learning by Allen, Cameron, Parikh, Neev, Gottesman, Omer, Konidaris, George

“…A fundamental assumption of reinforcement learning in Markov decision processes (MDPs) is that the relevant decision process is, in fact, Markov. However, when…”
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A general method for regularizing tensor decomposition methods via pseudo-data by Gottesman, Omer, Pan, Weiwei, Doshi-Velez, Finale

“…Tensor decomposition methods allow us to learn the parameters of latent variable models through decomposition of low-order moments of data. A significant…”
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Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy by Allen, Cameron, Kirtland, Aaron, Tao, Ruo Yu, Lobel, Sam, Scott, Daniel, Petrocelli, Nicholas, Gottesman, Omer, Parr, Ronald, Littman, Michael L, Konidaris, George

“…Reinforcement learning algorithms typically rely on the assumption that the environment dynamics and value function can be expressed in terms of a Markovian…”
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Learning to search efficiently for causally near-optimal treatments by Håkansson, Samuel, Lindblom, Viktor, Gottesman, Omer, Johansson, Fredrik D

“…Finding an effective medical treatment often requires a search by trial and error. Making this search more efficient by minimizing the number of unnecessary…”
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Faster Deep Reinforcement Learning with Slower Online Network by Asadi, Kavosh, Fakoor, Rasool, Gottesman, Omer, Kim, Taesup, Littman, Michael L, Smola, Alexander J

“…Deep reinforcement learning algorithms often use two networks for value function optimization: an online network, and a target network that tracks the online…”
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Identification of Subgroups With Similar Benefits in Off-Policy Policy Evaluation by Keramati, Ramtin, Gottesman, Omer, Celi, Leo Anthony, Doshi-Velez, Finale, Brunskill, Emma

“…Off-policy policy evaluation methods for sequential decision making can be used to help identify if a proposed decision policy is better than a current…”
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