Learning to Optimize Contextually Constrained Problems for Real-Time Decision Generation
References
- (2019) Differentiable convex optimization layers. Adv. Neural Inform. Processing Systems 32:9562–9574.Google Scholar
- (2017) Optnet: Differentiable optimization as a layer in neural networks. Proc. Internat. Conf. Machine Learn., vol. 70 (JMLR.org), 136–145.Google Scholar
- (2014) Business analytics for flexible resource allocation under random emergencies. Management Sci. 60(6):1552–1573.Link, Google Scholar
- (1988) Queries and concept learning. Machine Learn. 2(4):319–342.Crossref, Google Scholar
- (2017) Toward principled methods for training generative adversarial networks. Preprint, submitted January 17, https://arxiv.org/abs/1701.04862.Google Scholar
- (2018) Inverse optimization of objective function weights for treatment planning using clinical dose-volume histograms. Phys. Medical Biology 63(10):105004.Crossref, Google Scholar
- (2020) Knowledge-based automated planning with three-dimensional generative adversarial networks. Medical Phys. 47(2):297–306.Crossref, Google Scholar
- Badenbroek R, de Klerk E (2021) Complexity analysis of a sampling-based interior point method for convex optimization. Math. Oper. Res. 47(1):779–811.Google Scholar
- (2017) Quality-efficiency trade-offs in machine learning for text processing. Proc. IEEE Internat. Conf. Big Data (IEEE, New York), 897–904.Google Scholar
- (2018) The big data newsvendor: Practical insights from machine learning. Oper. Res. 1(67):90–108.Google Scholar
- (2018) Machine learning and portfolio optimization. Management Sci. 64(3):1136–1154.Link, Google Scholar
- (2019) Special issue on nonconvex portfolio optimization. Engrg. Econom. 64(3):193–195.Crossref, Google Scholar
- (2002) Rademacher and gaussian complexities: Risk bounds and structural results. J. Machine Learn. Res. 3(November):463–482.Google Scholar
- Bastani H, Bastani O, Kim C (2018) Interpreting predictive models for human-in-the-loop analytics. Accessed April 2, 2022, https://api.semanticscholar.org/CorpusID:53073710.Google Scholar
- Bello I, Pham H, Le QV, Norouzi M, Bengio S (2016) Neural combinatorial optimization with reinforcement learning. Preprint, submitted November 29, https://doi.org/10.48550/arXiv.1611.09940.Google Scholar
- (2010) A theory of learning from different domains. Machine Learn. 79(1):151–175.Crossref, Google Scholar
- (2011) Linking task conditions to physiology and judgment errors in rm systems. Production Oper. Management 20(6):860–876.Crossref, Google Scholar
- (2013) Real-time feedback and booking behavior in the hospitality industry: Moderating the balance between imperfect judgment and imperfect prescription. J. Oper. Management 31(1–2):62–71.Crossref, Google Scholar
- (2020) Machine learning for combinatorial optimization: A methodological tour d’horizon. Eur. J. Oper. Res. 290(2):405–421.Google Scholar
- (2004) Interior-point methods for nonconvex nonlinear programming: Jamming and numerical testing. Math. Programming 99(1):35–48.Crossref, Google Scholar
- (2022) A scalable algorithm for sparse portfolio selection. INFORMS J. Comput. 34(3):1489–1511.Link, Google Scholar
- (2019) From predictive to prescriptive analytics. Management Sci. 66(3):1025–1044.Google Scholar
- (2018) Optimization over continuous and multi-dimensional decisions with observational data. Adv. Neural Inform. Processing Systems 21:2966–2974.Google Scholar
- (2011) Theory and applications of robust optimization. SIAM Rev. 53(3):464–501.Crossref, Google Scholar
- (2020) Personalized treatment for coronary artery disease patients: A machine learning approach. Health Care Management Sci. 23(4):1–25.Google Scholar
- (2014) Stochastic multi-armed-bandit problem with non-stationary rewards. Adv. Neural Inform. Processing Systems 27:1–9.Google Scholar
- (2016) Sample size requirements for knowledge-based treatment planning. Medical Phys. 43(3):1212–1221.Crossref, Google Scholar
- (2004) Convex Optimization (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
- (2007) Notes on decomposition methods. Notes for EE364B, vol. 635 (Stanford University, Stanford, CA), 1–36.Google Scholar
- (2019) The entropic barrier: Exponential families, log-concave geometry, and self-concordance. Math. Oper. Res. 44(1):264–276.Abstract, Google Scholar
- (2004) Efficient insertion heuristics for vehicle routing and scheduling problems. Transportation Sci. 38(3):369–378.Link, Google Scholar
- (2021) Personalized robo-advising: Enhancing investment through client interaction. Management Sci. 68(4):2485–2512.Google Scholar
- (2017) Annotating object instances with a polygon-rnn. Proc. IEEE Conf. Comput. Vision Pattern Recognition (IEEE, Piscataway, NJ), 5230–5238.Google Scholar
- (2012) Optimizing intensive care unit discharge decisions with patient readmissions. Oper. Res. 60(6):1323–1341.Link, Google Scholar
- (2022) Hedging the drift: Learning to optimize under nonstationarity. Management Sci. 68(3):1696–1713.Link, Google Scholar
- (2006) Decomposition Techniques in Mathematical Programming: Engineering and Science Applications (Springer Science & Business Media, New York).Google Scholar
- (2015) How behavioral factors affect decisions related to work process deviation. Accessed November 25, 2020, https://www2.deloitte.com/za/en/insights/focus/behavioral-economics/applying-behavioral-principles-in-workplace.html.Google Scholar
- (2015) The missing piece in complex analytics: Low latency, scalable model management and serving with velox. Proc. 7th Biennial Conf. Innovative Data Systems Res. (www.cidrdb.org).Google Scholar
- (2008) Neurobiological studies of risk assessment: A comparison of expected utility and mean-variance approaches. Cognition Affective Behav. Neurosci. 8(4):363–374.Crossref, Google Scholar
- (2005) The role of radiotherapy in cancer treatment. Cancer 104(6):1129–1137.Crossref, Google Scholar
- (2017) Task-based end-to-end model learning in stochastic optimization. Adv. Neural Inform. Processing Systems 30:5484–5494.Google Scholar
- Elmachtoub AN, Grigas P (2021) Smart “predict, then optimize”. Management Sci. 68(1):9–26.Google Scholar
- (2019) Enabling the human in the loop: Linked data and knowledge in industrial cyber-physical systems. Annu. Rev. Control 47:249–265.Crossref, Google Scholar
- (2020) A clinician’s guide to artificial intelligence: How to critically appraise machine learning studies. Translation Vision Sci. Tech. 9(2):7–7.Crossref, Google Scholar
- Ferber A, Wilder B, Dilkina B, Tambe M (2020) Mipaal: Mixed integer program as a layer. Proc. AAAI Conf. Artificial Intelligence, vol. 34 (AAAI Press, Palo Alto, CA), 1504–1511.Google Scholar
- (2015) Analytics for an online retailer: Demand forecasting and price optimization. Manufacturing Services Oper. Management 18(1):69–88.Link, Google Scholar
- (2020) Predicting AC optimal power flows: Combining deep learning and Lagrangian dual methods. Proc. Conf. AAAI Artificial Intelligence (AAAI Press, Palo Alto, CA), 630–637.Google Scholar
- (2018) Uniform convergence of gradients for non-convex learning and optimization. Adv. Neural Inform. Processing Systems 31:8759–8770.Google Scholar
- (2015) Definitive intensity modulated radiotherapy in locally advanced hypopharygeal and laryngeal squamous cell carcinoma: Mature treatment results and patterns of locoregional failure. Radiation Oncology 10:20.Crossref, Google Scholar
- (2012) Interior point methods 25 years later. Eur. J. Oper. Res. 218(3):587–601.Crossref, Google Scholar
- (2016) Deep Learning, vol. 1 (MIT Press, Cambridge, MA).Google Scholar
- (2014) Generative adversarial nets. Adv. Neural Inform. Processing Systems 27:2672–2680.Google Scholar
- (2020) Small-data, large-scale linear optimization with uncertain objectives. Management Sci. 67(1):220–241.Link, Google Scholar
- Gurobi Optimization L (2020) Gurobi optimizer reference manual. http://www.gurobi.com.Google Scholar
- (2019) Deep self-learning from noisy labels. Proc. IEEE/CVF Internat. Conf. Comput. Vision (IEEE, Piscataway, NJ), 5138–5147.Google Scholar
- (2010) Nonparametric density estimation for stochastic optimization with an observable state variable. Adv. Neural Inform. Processing Systems 23:820–828.Google Scholar
- (1988) A General Theory of Equilibrium Selection in Games (MIT Press, Cambridge, MA).Google Scholar
- (2018) A one-phase interior point method for nonconvex optimization. Preprint, submitted January 11, https://arxiv.org/abs/1801.03072.Google Scholar
- (2015) A note on the sensitivity of the strategic asset allocation problem. Oper. Res. Perspective 2:133–136.Crossref, Google Scholar
- (2021) Wide-scale clinical implementation of knowledge-based planning: An investigation of workforce efficiency, need for post-automation refinement, and data-driven model maintenance. Internat. J. Radiation Oncology Biology Physics 111(3):705–715.Crossref, Google Scholar
- (2009) Directed regression. Adv. Neural Inform. Processing Systems 22:889–897.Google Scholar
- (2018) Dosenet: A volumetric dose prediction algorithm using 3d fully-convolutional neural networks. Phys. Medical Biology 63(23):235022.Crossref, Google Scholar
- (2019) Gan-MP hybrid heuristic algorithm for non-convex portfolio optimization problem. Engrg. Econom. 64(3):196–226.Crossref, Google Scholar
- (2000) Actor-critic algorithms. Adv. Neural Inform. Processing Systems 12:1008–1014.Google Scholar
- (2019) Attention, learn to solve routing problems! Proc. Internat. Conf. Learn. Representations (ICLR, Appleton, WI).Google Scholar
- (2021) Learning hard optimization problems: A data generation perspective. Adv. Neural Inform. Processing Systems 34:24981–24992.Google Scholar
- Lagzi S, Quiroga BF, Romero G, Howard N, Chan TC (2023) Negative externality on service level across priority classes: Evidence from a radiology workflow platform. J. Oper. Management 69(8):1257–1281.Google Scholar
- (2018) Should artificial intelligence augment medical decision making? The case for an autonomy algorithm. AMA J. Ethics 20(9):902–910.Crossref, Google Scholar
- (2018) Predicting solution summaries to integer linear programs under imperfect information with machine learning. Preprint, submitted July 31, https://doi.org/10.48550/arXiv.1807.11876.Google Scholar
- (2020) Inverse optimization of convex risk functions. Management Sci. 67(11):7113–7141.Google Scholar
- (2021) A review of industrial big data for decision making in intelligent manufacturing. Engrg. Sci. Tech. 29(101021):1–16.Google Scholar
- (2017) Learning from noisy labels with distillation. Proc. IEEE Internat. Conf. Comput. Vision (IEEE, Piscataway, NJ), 1910–1918.Google Scholar
- (2021) Toward good practices for efficiently annotating large-scale image classification datasets. Proc. IEEE/CVF Conference Computer Vision Pattern Recognition (IEEE, Piscataway, NJ), 4350–4359.Google Scholar
- (1998) A technique for the quantitative evaluation of dose distributions. Medical Phys. 25(5):656–661.Crossref, Google Scholar
- (2018) Automated treatment planning in radiation therapy using generative adversarial networks. Doshi-Velez F, Fackler J, Jung K, Kale D, eds. Proc. 3rd Machine Learning Healthcare Conf., vol. 85 (PMLR, New York), 484–499.Google Scholar
- (2016) A vector-contraction inequality for rademacher complexities. Proc. Internat. Conf. Algorithmic Learn. Theory (Springer, Berlin), 3–17.Google Scholar
- (2021) Reinforcement learning for combinatorial optimization: A survey Computers Oper. Res. 134:105400.Google Scholar
- (2021) A machine learning-based system for predicting service-level failures in supply chains. INFORMS J. Appl. Anal. 51(3):200–212.Link, Google Scholar
- (2020) Data analytics in operations management: A review. Manufacturing Service Oper. Management 22(1):158–169.Link, Google Scholar
- (2018) Learning fast optimizers for contextual stochastic integer programs. Proc. Thirty-Fourth Conf. Uncertainty Artificial Intelligence, UAI 2018 (Monterrey, CA).Google Scholar
- (2013) Learning with noisy labels. Adv. Neural Inform. Processing Systems 26:1196–1204.Google Scholar
- (1994) Interior-Point Polynomial Algorithms in Convex Programming, vol. 13 (SIAM, Philadelphia).Crossref, Google Scholar
- (2015) Norm-based capacity control in neural networks. Proc. Conf. Learn. Theory (PMLR, New York), 1376–1401.Google Scholar
- (2019) 3d radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected u-net deep learning architecture. Phys. Medical Biology 64(6):065020.Crossref, Google Scholar
- (2002) A survey of optimization by building and using probabilistic models. Comput. Optim. Appl. 21(1):5–20.Crossref, Google Scholar
- (2017) On the expressive power of deep neural networks. Proc. Internat. Conf. Machine Learn. (PMLR, New York), 2847–2854.Google Scholar
- (2022) A survey on domain adaptation theory. Preprint, submitted July 13, https://arxiv.org/abs/2004.11829.Google Scholar
- (2015) Facenet: A unified embedding for face recognition and clustering. Proc. IEEE Conf. Comput. Vision Pattern Recognition (IEEE, Piscataway, NJ), 815–823.Google Scholar
- (2009) Active learning literature survey. Technical report, University of Wisconsin-Madison, Department of Computer Sciences, Madison, WI.Google Scholar
- (2022) Calibrating sales forecast in a pandemic using competitive online non-parametric regression. Preprint, submitted April 11, https://dx.doi.org/10.2139/ssrn.3670264.Google Scholar
- (2017) Revisiting unreasonable effectiveness of data in deep learning era. Proc. IEEE Internat. Conf. Comput. Vision (IEEE, Piscataway, NJ), 843–852.Google Scholar
- (2018) Large-scale recommendation for portfolio optimization. Proc. 12th ACM Conf. Recommender Systems (ACM, New York), 382–386.Google Scholar
- (1999) An interior-point algorithm for nonconvex nonlinear programming. Comput. Optim. Appl. 13(1–3):231–252.Crossref, Google Scholar
- (2017) Extended formulations in mixed integer conic quadratic programming. Math. Programming Comput. 9(3):369–418.Crossref, Google Scholar
- (2015) Pointer networks. Adv. Neural Inform. Processing Systems 28:2692–2700.Google Scholar
- (2020) Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness. bmj 368.Google Scholar
- (2015) Active learning via query synthesis and nearest neighbour search. Neurocomputing 147:426–434.Crossref, Google Scholar
- (2012) How far can client-only solutions go for mobile browser speed? Proc. 21st Internat. Conf. World Wide Web (ACM, New York), 31–40.Google Scholar
- (2019) Melding the data-decisions pipeline: Decision-focused learning for combinatorial optimization. Proc. Conf. AAAI Artificial Intelligence (AAAI Press, Palo Alto, CA), 1658–1665.Crossref, Google Scholar
- (2015) Deep multiple instance learning for image classification and auto-annotation. Proc. IEEE Conf. Comput. Vision Pattern Recognition (IEEE, Piscataway, NJ), 3460–3469.Google Scholar
- (2017) Cross-institutional knowledge-based planning (KBP) implementation and its performance comparison with auto-planning engine (APE). J. Eur. Society Therapeutic Radiology Oncology 123(1):57–62.Crossref, Google Scholar
- Yu S, Wang H, Dong C (2023) Learning risk preferences from investment portfolios using inverse optimization. Res. Internat. Bus. Finance 64:101879.Google Scholar
- (2021a) Image gans meet differentiable rendering for inverse graphics and interpretable 3d neural rendering. Proc. Internat. Conf. Learn. Representations (OpenReview.net).Google Scholar
- (2021b) Datasetgan: Efficient labeled data factory with minimal human effort. Proc. IEEE Conf. Comput. Vision Pattern Recognition (IEEE, Piscataway, NJ).Google Scholar
- (2018) Leveraging program analysis to reduce user-perceived latency in mobile applications. Proc. 40th Internat. Conf. Software Engrg. (ACM, New York), 176–186.Google Scholar

