**Funding from NSF under
grants DMS-0595595, DMS-0806145 / 0902075, CAREER award CMMI-0846816,**
**CMMI-1069064, DMS-1320550, CMMI-1436700, is gratefully acknowledged.**

**Publications and Scholarly Works (in cronological order within sections)**

__Articles
in Journals (published or accepted for publication)__

__Articles in
Journals (submitted)__

__Conference
Proceedings (published or accepted for publication)__

__Book Chapters
and Encyclopedia Articles__

__Articles Submitted
for Publication__

**Many of the papers below take you to a link which includes a brief
explanation of the paper in an informal style. (All of them should have such
explanation soon.)**

1.
__Doctoral thesis title__

Limit Theorems and Approximations with Applications to
Insurance Risk and Queueing Theory (2004) Stanford University, Department
of Management Science and Engineering. Advisor, Professor Peter Glynn

2.
__Articles in Journals (published or accepted for
publication)__

** Denotes a publication given the 2009 Applied Probability Society Best Publication Award.

* Finalist paper in the 2010 INFORMS Junior Faculty Interest Group Forum Competition.

& Honorable mention in the 2011 INFORMS Nicholson Student Paper Competition (as supervisor).

% Finalist INFORMS 2010 Junior Faculty Interest Group competition.

Most links of
the published or accepted papers prompt to a summary page which includes a bibtex record and the paper.

1.
Pekoz, E., and Blanchet, J. Heavy-traffic
Limit Theorems via Embeddings. *Probability
in the Engineering and Informational Sciences*, 20 (2006), pp. 595-598

2.
Blanchet, J., and Glynn, P. Corrected
Diffusion Approximations for the Maximum of Light-tailed Random Walk. *Annals of Applied Probability*, 16
(2006), 2, pp. 952-983. (T)

3.
Blanchet, J., and Glynn, P. Uniform Renewal Theory with Applications to
Geometric Sums. *Advances in Applied
Probability*, 39 (2007), 4, pp 1070 – 1097.

4.
Blanchet, J., Glynn, P., and Liu, J. C. Fluid Heuristics, Lyapunov
Bounds and Efficient Importance Sampling for a Heavy-tailed G/G/1 Queue. *Queueing Systems: Theory and Applications*,
56 (2007), 3, pp. 99 – 113.** (S)

5. Blanchet, J. and Glynn, P. Efficient Rare Event Simulation for the Single Server Queue with Heavy Tailed Distributions. Annals of Applied Probability, 18 (2008), 4, pp. 1351 – 1378.**

6.
Blanchet, J., and Liu, J. C. State-dependent Importance Sampling for
Regularly Varying Random Walks. *Advances
in Applied Probability*, 40, (2008), pp 1104-1128. (S)

7.
Asmussen, S., Blanchet, J.,
Rojas-Nandayapa, L., and Juneja,
S. Efficient Simulation of Tails
Probabilities of Sums of Correlated Lognormals. To appear in *Annals of Operations Research*, Special
vol. in honor of Reuven Rubinstein.

8.
Blanchet, J., Glynn, P., and Lam, H. Rare-event Simulation of a Slotted Time
M/G/s Queue. *Queueing Systems: Theory
and Applications*, 67, (2009), pp 33 – 57. (S), (I)

9.
Olvera-Cravioto, M., Blanchet,
J. and Glynn P. On the Transition from
Heavy Traffic to Heavy Tails for the M/G/1 Queue I: The Regularly Varying Case. *Annals of Applied Probability*, 21,
(2011), pp 645-668. (C)

10. Blanchet,
J. Importance Sampling and Efficient
Counting for Binary Contingency Tables. *Annals
of Applied Probability*, 19, (2009), pp 949 – 982.**

11. Blanchet,
J., and Li, C. Efficient Rare-event
Simulation for Heavy-tailed Compound Sums. *ACM TOMACS Transactions in Modeling and Computer Simulation*, 21,
(2011), pp 1-10.

12. Blanchet,
J., and Li, C. Efficient Simulation
for the Maximum of Infinite Horizon Gaussian Processes. To appear in *Journal of Applied Probability. *(S)

13. Blanchet,
J. and Liu, J. Efficient
Importance Sampling in Ruin Problems for Multidimensional Regularly Varying
Random Walks. *Journal of Applied
Probability*, 47, (2010), 301-322.* (S)

14. Blanchet,
J. and Zwart, B. Asymptotic Expansions of Renewal Equations
with Applications to Insurance and Processor Sharing. *Math. Meth. in Oper.
Res.*, 72, (2010), 311-326.

15. L'Ecuyer, P., Blanchet, J., Tuffin,
B., and Glynn, P. W. Asymptotic Robustness of Estimators in
Rare-Event Simulation. *ACM TOMACS
Transactions in Modeling and Computer Simulation*, 20, (2010), pp 1-41.

16. Lam,
H. K., Blanchet, J., Bazant, M., and Burch, D. Corrections to the Central Limit
Theorem for Heavy-tailed Probability Densities. To appear in *Journal of Theoretical Probability*.
(Available through on-line first since September 17, 2011.) (S)

17. Blanchet,
J., Leder, K., Shi, Y. Analysis of a Splitting Estimator for Rare
Event Probabilities in Jackson Networks. *Stochastic Systems, *1, (2011), pp 306-339.* *(P, S)

18. Blanchet,
J., and Rojas-Nandayapa, L. Efficient Simulation of Tail
Probabilities of Sums of Dependent Random Variables.* Journal of Applied
Probability, Special Vol. 48A, *(2011), 147-165.

19. Blanchet,
J., and Sigman, K. On
Exact Sampling of Stochastic Perpetuities. *Journal of Applied
Probability, Special Vol. 48A, *(2011), 165-183. (C)

20. Blanchet,
J., and Lam, H. State-dependent Importance
Sampling for Rare Event Simulation: An Overview and Recent advances. *Surveys in Operations Research and
Management Sciences, *17*, *(2012),
38-59 (S)

21. Adler,
R., Blanchet, J., and Liu, J. C. Efficient
Simulation of High Excursions of Gaussian Random Fields. *Annals of Applied Probability*, 22,
(2012), 1167-1214. (S)

22. Blanchet,
J.** **and Pacheco-Gonzales, C. Uniform Convergence to a Law
Containing Gaussian and Cauchy Distributions. *Probability in the Engineering and Informational Sciences,* 26,* *(2012), 437-448

23. Blanchet,
J., and Stauffer, A. Characterizing
Optimal Sampling of Binary Contingency Tables via the Configuration Model. *Random Structures and Algorithms,* 42,
159-184 (2012). (See also http://arxiv.org/abs/1007.1214.)

*24. *Blanchet,
J., Glynn, P., and Leder, K. On Lyapunov Inequalities and Subsolutions
for Efficient Importance Sampling. *ACM
TOMACS* *Transactions in Modeling and
Computer Simulation, *22, (2012). Article No. 13.

**25. **Blanchet,
J., Lam, H., and Zwart, B. Efficient Rare Event Simulation for
Perpetuities.* Stochastic Processes
and their Applications, *122, (2012), 3361-3392. (S)

26. Blanchet,
J. Optimal Sampling of Overflow Paths in
Jackson Networks. * Mathematics of Operations Research, *38,** **(2013**)**, 698-719.

27. Blanchet,
J., and Liu, J. C. Efficient Simulation
and Conditional Functional Limit Theorems for Ruinous Heavy-tailed Random Walks.
*Stochastic Processes and their
Applications*, 122, (2012), 2994-3031. (S)

28. Blanchet,
J.** **and Shi, Y. Strongly Efficient Algorithms via Cross
Entropy for Heavy- tailed Systems. *Operations
Research Letters*, 41, (2013), 271-276. (S)

29. Blanchet,
J., and Liu, J. C. Total
Variation Approximations for Multivariate Regularly Varying Random Walks
Conditioned on Ruin. *Bernoulli*,
20, (2014), 416-456. (S)

30. Blanchet,
J., Glynn, P., and Meyn, S. Large Deviations for the Empirical
Mean of an M/M/1 Queue. *Queueing
Systems: Theory and Applications, *73, (2013), 425-446.

31. Blanchet,
J.** **and Lam, H. A Heavy Traffic Approach to Modeling Large Life
Insurance Portfolios. *Insurance:
Mathematics and Economics*, 53, (2013), 237-251. (S)

32. Blanchet,
J. and Mandjes, M. Asymptotics of the Area under the Graph of a Lévy-driven Workload Process. *Operations Research Letters*, 41, (2013), 730-736.

33. Blanchet,
J., Hult, H., and Leder, K.
Rare-event simulation for
stochastic recurrence equations with heavy-tailed innovations. *ACM TOMACS Transactions on Modeling and
Computer Simulations. *(Supplement), 23,
(2013), Article No. 22.

34. Blanchet,
J., and Lam, H. Rare-event Simulation
for Many Server Queues. *Mathematics
of Operations Research*, 39, (2014), 1142–1178. (S)

35. Blanchet,
J., Chen, X., and Lam, H. Two-parameter
Sample Path Large Deviations for Infinite Server Queues. *Stochastic Systems,* 4, (2014),
206-249*.*

36. Blanchet,
J.** **and Lam, H. Uniform Large Deviations for Heavy-Tailed
Queues under Heavy-Traffic. *Bulletin
of the Mexican Mathematical Society*, Bol. Soc. Mat. Mexicana (3) Vol. 19,
2013 Special Issue for the International Year of Statistics.

37. Blanchet,
J.** **and Chen, X. Steady-state
Simulation for Reflected Brownian Motion and Related Networks. To appear *Annals of Applied Probability.*__ __

38. Murthy,
K.,** **Juneja,
S., and Blanchet, J.** **State-independent Importance Sampling for Random
Walks with Regularly Varying Increments. To appear *Stochastic Systems.*

39. Blanchet,
J. and Dong, J. Perfect
Sampling for Infinite Server and Loss Systems. *Advances in Applied Probability*, 47, (2015).

40. Blanchet,
J.** **and Wallwater,
A. Exact Sampling for the
Steady-state Waiting Time of a Heavy-tailed Single Server Queue. *ACM TOMACS Transactions on Modeling and
Computer Simulations*, 25 (4) (2015)
http://dl.acm.org/citation.cfm?id=2822892&CFID=594568455&CFTOKEN=74958442

41. Blanchet,
J., Gallego, G. and Goyal, V. A Markov Chain Approximation to Choice Modeling.
To appear in *Operations Research* (http://pubsonline.informs.org/doi/abs/10.1287/opre.2016.1505?journalCode=opre
).

42. Zhang, X., Blanchet,
J., Giesecke, K., and Glynn, P. Affine Point Processes: Approximation and Efficient
Simulation. To appear in *Mathematics
of Operations Research.*

43. Blanchet,
J.**,** and Murthy, K. Tail Asymptotics
for Large Delays in a Half-Loaded GI/GI/2 Queue with Heavy-Tailed Job Sizes.
*Queueing Systems: Theory and
Applications, *81, (2015), 301-340*.*

44. Bienstock, D., Li, J., and Blanchet, J.** **Stochastic Models
and Control for Electrical Power Line Temperature. *Energy Systems, *7, (2016), 173-192.** **

45. Blanchet,
J. and Ruf, J. A Weak Convergence Criterion
Constructing Changes of Measure. *Stochastic
Models, *22, (2016). http://www.tandfonline.com/doi/abs/10.1080/15326349.2015.1114891?journalCode=lstm20

46. Blanchet,
J.**, **Glynn, P., and Zheng, J. __Theoretical Analysis of a Stochastic
Approximation Approach for Computing Quasi-stationary Distributions__. *Advances in Applied Probability*, 48,
(2016) 792-811.

47. Blanchet,
J., Chen, X., and Dong, J. ε-Strong Simulation of
Multidimensional Stochastic Differential Equations via Rough Path Analysis.
*Annals of Applied Probability*, 27,
(2017), 275-339. http://arxiv.org/abs/1403.5722

3.
__Articles submitted or under review__

48. Blanchet,
J. and Murthy, K. __Exact Simulation of Multidimensional
Reflected Brownian Motion__.

49. Blanchet,
J., and Zhang, F. Exact
Simulation for Multivariate Ito Diffusions

50. Blanchet,
J.**, **Dong, J., and Pei, Y. __Perfect Sampling of G/G/c Queues.__

51. Blanchet,
J.**, **Pei, Y., Sigman,
K. Exact sampling for
some multi-dimensional queueing models with renewal input

52. Liu, Z., Blanchet,
J., Dieker, T., and Mikosch,
T. On
Optimal Exact Simulation of Max-stable and Related Random Fields on a Compact
Set

53. Blanchet,
J.** **and Liu, Z. Malliavin-based
Multilevel Monte Carlo Estimators for Densities of Max-stable Processes

54. Blanchet,
J., Dong, J., and Liu, Z. Exact Sampling
of the Infinite Horizon Maximum of a Random Walk over a Non-linear Boundary

55. Blanchet,
J., Li, J., and Nakayama, M. __Efficient Monte Carlo Methods
for Estimating Failure Probabilities of a Distribution Network with Random
Demands__.

56. Rhee, C-H.,
Blanchet, J., and Zwart, B. Sample Path Large Deviations for Heavy-Tailed Lévy Processes and Random Walks

57. Bohan, Blanchet, J., Rhee, C-H., and Zwart,
B. Efficient Rare-Event Simulation for
Multiple Jump Events in Regularly Varying Random Walks and Compound Poisson Processes

58. Blanchet,
J., and Chen, X., Rates of
Convergence to Stationarity for Multidimensional RBM

59. Blanchet,
J., and Chen, X., Perfect Sampling of
Generalized Jackson Networks

60. Blanchet,
J., Lam, H., Tang, Q., and Yuan, Z. Applied Robust Performance Analysis for
Actuarial Applications** **

61. Blanchet,
J.** **and Kang, Y. Sample-out-of-sample Inference Based on Wasserstein
Distance

62. Blanchet,
J.** **and Murthy, K. Quantifying Distributional Model Risk via
Optimal Transport

63. Blanchet,
J.** **and Murthy, K. On Distributionally
Robust Extreme Value Theory__ __

64. Blanchet, J., and Chen, X., Pei, Y. Unraveling Limit Order Books Using Just Bid/Ask Prices

65. Blanchet, J., Kang, Y., Murthy, K. Robust Wasserstein Profile Inference and Applications to Machine Learning

66. Blanchet,
J.**, **Cartis,
C., Menickelly, M., and Scheinberg,
K. Convergence Rate Analysis of a
Stochastic Trust Region Method for Nonconvex Optimization.

67. Blanchet, J., and Kang, Y. Semi-supervised Learning based on Distributionally Robust Optimization (also posted in ArXiv as Distributionally Robust Semi-supervised Learning)

68. Blanchet, J., Kang, Y., Zhang, F., and Murthy, K. Data-driven Optimal Transport Cost Selection for Distributionally Robust Optimization

69. Blanchet, J., Kang, Y., Zhang, F., He, F., and Hu, Z. Doubly Robust Data-Driven Distributionally Robust Optimization

4.
__Conference Proceedings (published or accepted for
publication)__

Note: + represents a paper for which there is journal version listed above, otherwise there is no overlap in content with papers that have appeared in journals.

70. Blanchet, J., and Glynn, P. Strongly-efficient Estimators for Light-tailed Sums. ACM: Proc Valuetools’06, Article 18, (2006). (S)

71. Blanchet, J., Liu, J. C. and Glynn, P. Importance Sampling and Large Deviations. Proc. Valuetools’06, Article 20, (2006). (S)

72. Blanchet, J., and Liu, J. C. Efficient Simulation of Large Deviation Probabilities for Sums of Heavy-tailed Increments. Proc. Winter Simulation Conference (2006), pp. 757-764. (S) +

73. Blanchet, J., and Zwart, B. Importance Sampling of Compounding Processes. Proc. Winter Simulation Conference (2007), pp. 372-379. (I) +

74. Blanchet, J., and Liu, J. C. Rare-event Simulation of Multidimensional Random Walks with t-distributed Increments. Proc. Winter Simulation Conference (2007), pp. 395-402. (S) (I) +

75. Blanchet, J., and Liu, J. C. Path-sampling for State-dependent Importance Sampling. Proc. Winter Simulation Conference (2007), pp. 380-388. (S) (I)

76. Zhang, X., Blanchet, J., and Glynn, P. Efficient Suboptimal Rare-event Simulation. Proc. Winter Simulation Conference (2007), pp. 389-394. (I)

77. Blanchet, J., Rojas-Nandayapa, L., and Juneja, S. Fast Simulation of Sums of Correlated Lognormals. Proc. Winter Simulation Conference (2008), pp. 607-614. +

78. Adler, R., Blanchet, J. and Liu, J. C. Efficient Simulation for Tail Probabilities of Gaussian Random Fields. Proc. Winter Simulation Conference (2008), pp 328-336. (S) (I) +

79. Blanchet, J., Liu, J. C., and Zwart, B. A Large Deviations Perspective to Ordinal Optimization of Heavy-tailed Systems. Proc. Winter Simulation Conference (2008), pp. 489-494. (S) (I)

80. Blanchet, J., Leder, K. and Glynn, P. Efficient Simulation for Light-tailed Sums: An Old Folk Song Sung to a Faster New Tune. Springer volume for MCQMC 2008 edited by Pierre L’Ecuyer and Art Owen. (2009), pp. 227-248. (P)

81. Blanchet, J., and Glynn, P. Efficient Rare Event Simulation of Continuous Time Markovian Perpetuities. Proc. Of the Winter Simulation Conference (2009), pp. 444-451. (I)

82. Zhang, X., Glynn, P., Giesecke, K., Blanchet, J. Rare Event Simulation of a Generalized Hawkes Process. Proc. Of the Winter Simulation Conference (2009), pp. 1291-1298. (I)

83. Blanchet, J., Liu, J. C., and Xang, X. Monte Carlo for Large Credit Portfolios with Potentially High Correlations. Proc. of the Winter Simulation Conference (2010), pp. 328-336. (S) (I)

84. Blanchet, J., and Lam, H. Rare Event Simulation Techniques. Proc. Winter Simulation Conference (2011). (S) (I)

85. Blanchet, J., and Shi, Y. Strongly Efficient Cross Entropy Method for Heavy-tailed Simulation, Winter Simulation Conference (2011). (S) (I)

86. Blanchet, J., Li, Juan, and Nakayama, M. A Conditional Monte Carlo for Estimating the Failure Probability of a Network with Random Demands (2011). (S) (I)

87. Blanchet, J., Hult, H., and Leder, K. Efficient Importance Sampling for Affine Regularly Varying Markov Chains (2011).

88. Blanchet,
J.**,** and Lam, H. Importance Sampling for Actuarial Cost
Analysis under a Heavy Traffic Model. Proc.
Winter Simulation Conference (2011). (S) (I)

89. Blanchet,
J.**,** and Dong, J. Sampling point processes on stable
unbounded regions and exact simulation of queues. Proc. Winter Simulation
Conference (2012): 11 (S) (I)

90. Blanchet,
J.**,** Glynn, P., and Zheng, S. Empirical Analysis of a Stochastic
Approximation Approach for Computing Quasi-stationary Distributions. EVOLVE
2012: 19-37

91. Blanchet,
J.**,** Gallego,
G., and Goyal, G. A
Markov chain approximation to choice modeling. ACM Conference on Electronic
Commerce 2013: 103-104

92. Blanchet, J. and Shi, Y. Efficient Rare Event Simulation via Particle Methods for Heavy-tailed Sums. Proc. Winter Simulation Conference (2013), pp. 724-735.

93. Blanchet, J., Murthy, K., and Juneja, S. Optimal Rare Event Monte Carlo for Markov Modulated Regularly Varying Random Walks. Proc. Winter Simulation Conference (2013), 564-576.

94. Bienstock, D., Blanchet, J., and Li, J. __Stochastic Models and Control
for Electrical Power Line Temperature.__ Proc. 51^{st} Annual
Allerton Conference on Communication, Control, and Computing (2013), 1344-1348.

95. Blanchet,
J., Dolan, C., and Lam, H. __Robust
Rare-Event Performance Analysis with Natural Non-Convex Constraints.__
Proc. Winter Simulation Conference (2014), pp. 595-603.

96. Shanbhag, U., and Blanchet, J. __Budget-Constrained Stochastic
Approximation__. Proc. Winter Simulation Conference (2015), 368-379.

97. Blanchet,
J., Chen, N., and Glynn, J. __Unbiased Monte Carlo
Computation of Smooth Functions of Expectations via Taylor Expansions__.
Proc. Winter Simulation Conference (2015), 360-367.

98. Blanchet,
J., and Glynn, J. __Unbiased Monte
Carlo for Optimization and Functions of Expectations via Multilevel
Randomization__. Proc. Winter Simulation Conference (2015), 3656-3667.

99. Blanchet,
J., He, F., and Lam, H. Computing Worst Case
Expectations Given Marginals via Simulation.
Proc. Winter Simulation Conference (2017), to appear.

100.
Blanchet, J., and Kang, Y. Distributionally
Robust Groupwise Regularization Estimator (2017),
to appear.

5.
__Chapters in Books (published or accepted for
publication)__

101. Blanchet, J., and Rudoy, D. Rare-event Simulation and Counting Problems. In Rare-event Estimation using Monte Carlo Methods, Rubino, G. and Tuffin, B. Eds. Wiley, 2009.

102. Blanchet, J., and Mandjes, M. Rare-event Simulation for Queues. In Rare-event Estimation using Monte Carlo Methods, Rubino, G. and Tuffin, B. Eds. Wiley, 2009.

103. Blanchet, J. and Pacheco-Gonzales C. Large Deviations and Applications to Quantitative Finance. Encyclopedia of Quantitative Finance, Edited by Rama Cont. Wiley 2009.

104.
Blanchet, J., and Mandjes, M.
Rare-event Simulation for Queues (2007). *Queueing
Systems: Theory and Applications*. Vol. 57 Numbers 2 and 3. Editorial.

105.
Blanchet, J., and Roberts, G. Simulation of Stochastic
Networks and related topics (2012). *Queueing
Systems: Theory and Applications*. Vo. 73 Numbers 4. Editorial.

7.
__Some Preprints and Technical Reports. BEWARE the
presentation requires polishing, but the math should be fine – however, I’d
appreciate comments if you see any problem. Also, please, email me if you’re
interested in any of the preprints below and it is not uploaded.__

106.
Blanchet, J., Liu, J. C., and Glynn, P. Efficient Rare Event Simulation for Regularly
Varying Multi-server Queues. To be submitted to *Queueing Systems Theory and Applications.* Summary: This paper provides the first
asymptotically optimal (in fact we show strong optimality) algorithm for
estimating the tails of the steady-state delay in a multi-server queue with
heavy-tailed increments. The technique is the one introduced in “Fluid Heuristics, Lyapunov Bounds and Efficient Importance Sampling for a
Heavy-tailed G/G/1 Queue (with P. Glynn, and J. C. Liu), 2007.
QUESTA, 57, 99-113”. The construction in the multidimensional case is
interesting because of the way in which fluid heuristics need to adapt to
accommodate the boundaries.

107.
Blanchet, J.** **and
Glynn, P.** **Large
Deviations and Sharp Asymptotics for Perpetuities
with Small Discount Rates . Summary: This paper relates to Approximations
for the Distribution of Perpetuities with Small Discount Rates (with P. Glynn).
Instead of concentrating on the central limit theorem region we develop large
deviations asymptotics. The paper contains
characterizations of exponential tightness in a suitable (and useful for the
analysis of perpetuities) class of topologies. It also develops exact tail asymptotics for discrete and continuous perpetuities and it
shows qualitative differences arising from the discrete and continuous nature
of perpetuities. I think this line of research is particularly interesting
these days in which the interest rates are small.

108.
Blanchet, J.**
**and Glynn, P. Corrected Diffusion Approximations for the Maximum of
Random Walks with Heavy-tails (with P. Glynn). *(Please, refer to
Chapter 3 of my dissertation for more details).* Summary: This paper
continues the study of corrected diffusion approximations for first passage
times of random walks with a small negative drift $mu$. The paper “Complete
Corrected Diffusion Approximations for the Maximum of Random Walk (2006) Ann.
of App. Prob., (with P. Glynn)” assumes finite exponential moments. Here we
show that if one has $alpha + 2$ moments then one can add $alpha$ correction
terms resulting in an approximation with an error of size o(mu^alpha).

109.
Blanchet, J.**,**
and Lam, H. K. Corrected
Diffusion Approximations for Moments of the Steady-state Waiting Time in a
G/G/1 Queue. Summary: This paper revisits Complete Corrected
Diffusion Approximations for the Maximum of Random Walk (with P.
Glynn), 2006. Ann. of App. Prob., 16, p. 951-953. We now concentrate on moments
rather than the tail of the distribution. Recently Janssen and van Leeuwaarden (2007), Stoch. Proc.
and their Appl., 117, 1928-1959, obtained complete asymptotic expansions for
the Gaussian case. Here we obtain expansions for any strongly non-lattice
distribution exponentially decaying tails.

110.
Blanchet, J.**,**
and Lam, H. K. Rare-event
Simulation for Markov Modulated Heavy-tailed Random Walks. Summary: This
paper considers rare-event simulation for first passage time probabilities of
Markov modulated regularly varying random walks. We use the Lyapunov-bound
technique to design the importance sampling estimator. What is interesting is
that the Lyapunov bound, instead of being tested in
one step of the underlying process, as we typically do, it must be tested after
K steps (for K large enough) or at regeneration times of the underlying Markov
modulation.

111.
Blanchet, J.**,**
and Meng, X. L. Exact Sampling,
Regeneration and Minorization Conditions. Summary: This
report builds on a paper by Asmussen, Glynn and Thorisson (1992) TOMACS. Here we note that if one has a
Harris chain with regeneration time “tau” and if one can compute a constant
C>0 such that E(tau^p)<=C
for p>1 (or Eexp(delta*tau)<C) then one can
generate exact samples from the
steady-state distribution of chain in question in finite time almost surely,
provided that one can identify the regeneration times of the chain.
Unfortunately, although the expected termination time will typically be
infinite. However, I recently figured out how to fix the problem for a large
class of chains, I hope to report on that in the not-so-distant future.

112.
Blanchet, J. and Shi, Y. Modeling and Efficient
Rare Event Simulation of Systemic Risk in Insurance-Reinsurance Networks.

113. Blanchet, J., and Glynn, P. Approximations for the Distribution of Perpetuities with Small Interest Rates.

114. Blanchet, J. and Dupuis, P. Fast Simulation of Brownian Motion Avoiding Random Obstacles.